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segformer-b0-finetuned-segments-sidewalk-oct-22

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  1. README.md +168 -195
  2. config.json +144 -0
  3. model.safetensors +3 -0
  4. runs/Sep30_01-33-27_88153ec10635/events.out.tfevents.1727660022.88153ec10635.2395.0 +3 -0
  5. training_args.bin +3 -0
README.md CHANGED
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  library_name: transformers
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- tags: []
 
 
 
 
 
 
 
 
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- # Model Card for Model ID
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- <!-- Provide a quick summary of what the model is/does. -->
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- ## Model Details
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- ### Model Description
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- This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generated.
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- ## Uses
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- <!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
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- ### Direct Use
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- ### Downstream Use [optional]
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- ### Out-of-Scope Use
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- ## Bias, Risks, and Limitations
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- ### Recommendations
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- Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
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- ## How to Get Started with the Model
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- Use the code below to get started with the model.
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- ## Training Details
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- ### Training Data
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- ### Training Procedure
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- <!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->
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- #### Preprocessing [optional]
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- [More Information Needed]
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- #### Training Hyperparameters
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- - **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
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- #### Speeds, Sizes, Times [optional]
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- <!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
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- ## Evaluation
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- <!-- This section describes the evaluation protocols and provides the results. -->
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- ### Testing Data, Factors & Metrics
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- #### Testing Data
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- #### Factors
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- #### Metrics
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- ### Results
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- #### Summary
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- ## Model Examination [optional]
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- ## Environmental Impact
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- Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).
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- ## Technical Specifications [optional]
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- ### Model Architecture and Objective
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- ## Glossary [optional]
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  ---
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  library_name: transformers
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+ license: other
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+ base_model: nvidia/mit-b0
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+ tags:
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+ - vision
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+ - image-segmentation
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+ - generated_from_trainer
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+ model-index:
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+ - name: segformer-b0-finetuned-segments-sidewalk-oct-22
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+ results: []
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  ---
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+ <!-- This model card has been generated automatically according to the information the Trainer had access to. You
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+ should probably proofread and complete it, then remove this comment. -->
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+
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+ # segformer-b0-finetuned-segments-sidewalk-oct-22
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+
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+ This model is a fine-tuned version of [nvidia/mit-b0](https://huggingface.co/nvidia/mit-b0) on the segments/sidewalk-semantic dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.9415
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+ - Mean Iou: 0.1739
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+ - Mean Accuracy: 0.2202
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+ - Overall Accuracy: 0.7714
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+ - Accuracy Unlabeled: nan
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+ - Accuracy Flat-road: 0.8361
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+ - Accuracy Flat-sidewalk: 0.9327
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+ - Accuracy Flat-crosswalk: 0.0
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+ - Accuracy Flat-cyclinglane: 0.4491
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+ - Accuracy Flat-parkingdriveway: 0.0618
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+ - Accuracy Flat-railtrack: nan
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+ - Accuracy Flat-curb: 0.0106
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+ - Accuracy Human-person: 0.0
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+ - Accuracy Human-rider: 0.0
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+ - Accuracy Vehicle-car: 0.8757
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+ - Accuracy Vehicle-truck: 0.0
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+ - Accuracy Vehicle-bus: 0.0
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+ - Accuracy Vehicle-tramtrain: nan
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+ - Accuracy Vehicle-motorcycle: 0.0
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+ - Accuracy Vehicle-bicycle: 0.0
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+ - Accuracy Vehicle-caravan: 0.0
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+ - Accuracy Vehicle-cartrailer: 0.0
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+ - Accuracy Construction-building: 0.8775
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+ - Accuracy Construction-door: 0.0
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+ - Accuracy Construction-wall: 0.0398
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+ - Accuracy Construction-fenceguardrail: 0.0000
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+ - Accuracy Construction-bridge: 0.0
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+ - Accuracy Construction-tunnel: nan
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+ - Accuracy Construction-stairs: 0.0
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+ - Accuracy Object-pole: 0.0
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+ - Accuracy Object-trafficsign: 0.0
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+ - Accuracy Object-trafficlight: 0.0
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+ - Accuracy Nature-vegetation: 0.9075
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+ - Accuracy Nature-terrain: 0.9080
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+ - Accuracy Sky: 0.9280
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+ - Accuracy Void-ground: 0.0
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+ - Accuracy Void-dynamic: 0.0
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+ - Accuracy Void-static: 0.0
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+ - Accuracy Void-unclear: 0.0
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+ - Iou Unlabeled: nan
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+ - Iou Flat-road: 0.5895
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+ - Iou Flat-sidewalk: 0.7842
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+ - Iou Flat-crosswalk: 0.0
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+ - Iou Flat-cyclinglane: 0.4140
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+ - Iou Flat-parkingdriveway: 0.0569
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+ - Iou Flat-railtrack: nan
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+ - Iou Flat-curb: 0.0105
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+ - Iou Human-person: 0.0
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+ - Iou Human-rider: 0.0
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+ - Iou Vehicle-car: 0.6473
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+ - Iou Vehicle-truck: 0.0
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+ - Iou Vehicle-bus: 0.0
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+ - Iou Vehicle-tramtrain: nan
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+ - Iou Vehicle-motorcycle: 0.0
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+ - Iou Vehicle-bicycle: 0.0
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+ - Iou Vehicle-caravan: 0.0
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+ - Iou Vehicle-cartrailer: 0.0
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+ - Iou Construction-building: 0.5914
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+ - Iou Construction-door: 0.0
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+ - Iou Construction-wall: 0.0393
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+ - Iou Construction-fenceguardrail: 0.0000
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+ - Iou Construction-bridge: 0.0
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+ - Iou Construction-tunnel: nan
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+ - Iou Construction-stairs: 0.0
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+ - Iou Object-pole: 0.0
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+ - Iou Object-trafficsign: 0.0
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+ - Iou Object-trafficlight: 0.0
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+ - Iou Nature-vegetation: 0.7895
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+ - Iou Nature-terrain: 0.6699
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+ - Iou Sky: 0.7975
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+ - Iou Void-ground: 0.0
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+ - Iou Void-dynamic: 0.0
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+ - Iou Void-static: 0.0
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+ - Iou Void-unclear: 0.0
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+
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+ ## Model description
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+ More information needed
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+ ## Intended uses & limitations
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+ More information needed
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+ ## Training and evaluation data
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+ More information needed
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+ ## Training procedure
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+ ### Training hyperparameters
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+ The following hyperparameters were used during training:
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+ - learning_rate: 6e-05
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+ - train_batch_size: 2
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+ - eval_batch_size: 2
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+ - seed: 42
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+ - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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+ - lr_scheduler_type: linear
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+ - num_epochs: 2
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+
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+ ### Training results
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+
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+ | Training Loss | Epoch | Step | Validation Loss | Mean Iou | Mean Accuracy | Overall Accuracy | Accuracy Unlabeled | Accuracy Flat-road | Accuracy Flat-sidewalk | Accuracy Flat-crosswalk | Accuracy Flat-cyclinglane | Accuracy Flat-parkingdriveway | Accuracy Flat-railtrack | Accuracy Flat-curb | Accuracy Human-person | Accuracy Human-rider | Accuracy Vehicle-car | Accuracy Vehicle-truck | Accuracy Vehicle-bus | Accuracy Vehicle-tramtrain | Accuracy Vehicle-motorcycle | Accuracy Vehicle-bicycle | Accuracy Vehicle-caravan | Accuracy Vehicle-cartrailer | Accuracy Construction-building | Accuracy Construction-door | Accuracy Construction-wall | Accuracy Construction-fenceguardrail | Accuracy Construction-bridge | Accuracy Construction-tunnel | Accuracy Construction-stairs | Accuracy Object-pole | Accuracy Object-trafficsign | Accuracy Object-trafficlight | Accuracy Nature-vegetation | Accuracy Nature-terrain | Accuracy Sky | Accuracy Void-ground | Accuracy Void-dynamic | Accuracy Void-static | Accuracy Void-unclear | Iou Unlabeled | Iou Flat-road | Iou Flat-sidewalk | Iou Flat-crosswalk | Iou Flat-cyclinglane | Iou Flat-parkingdriveway | Iou Flat-railtrack | Iou Flat-curb | Iou Human-person | Iou Human-rider | Iou Vehicle-car | Iou Vehicle-truck | Iou Vehicle-bus | Iou Vehicle-tramtrain | Iou Vehicle-motorcycle | Iou Vehicle-bicycle | Iou Vehicle-caravan | Iou Vehicle-cartrailer | Iou Construction-building | Iou Construction-door | Iou Construction-wall | Iou Construction-fenceguardrail | Iou Construction-bridge | Iou Construction-tunnel | Iou Construction-stairs | Iou Object-pole | Iou Object-trafficsign | Iou Object-trafficlight | Iou Nature-vegetation | Iou Nature-terrain | Iou Sky | Iou Void-ground | Iou Void-dynamic | Iou Void-static | Iou Void-unclear |
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+ |:-------------:|:-----:|:----:|:---------------:|:--------:|:-------------:|:----------------:|:------------------:|:------------------:|:----------------------:|:-----------------------:|:-------------------------:|:-----------------------------:|:-----------------------:|:------------------:|:---------------------:|:--------------------:|:--------------------:|:----------------------:|:--------------------:|:--------------------------:|:---------------------------:|:------------------------:|:------------------------:|:---------------------------:|:------------------------------:|:--------------------------:|:--------------------------:|:------------------------------------:|:----------------------------:|:----------------------------:|:----------------------------:|:--------------------:|:---------------------------:|:----------------------------:|:--------------------------:|:-----------------------:|:------------:|:--------------------:|:---------------------:|:--------------------:|:---------------------:|:-------------:|:-------------:|:-----------------:|:------------------:|:--------------------:|:------------------------:|:------------------:|:-------------:|:----------------:|:---------------:|:---------------:|:-----------------:|:---------------:|:---------------------:|:----------------------:|:-------------------:|:-------------------:|:----------------------:|:-------------------------:|:---------------------:|:---------------------:|:-------------------------------:|:-----------------------:|:-----------------------:|:-----------------------:|:---------------:|:----------------------:|:-----------------------:|:---------------------:|:------------------:|:-------:|:---------------:|:----------------:|:---------------:|:----------------:|
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+ | 2.9835 | 0.05 | 20 | 3.2065 | 0.0687 | 0.1233 | 0.5589 | nan | 0.2838 | 0.8965 | 0.0069 | 0.0036 | 0.0007 | nan | 0.0008 | 0.0172 | 0.0 | 0.8081 | 0.0 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.8197 | 0.0 | 0.0110 | 0.0014 | 0.0 | nan | 0.0030 | 0.0084 | 0.0 | 0.0 | 0.6134 | 0.1250 | 0.2229 | 0.0 | 0.0 | 0.0012 | 0.0 | 0.0 | 0.2033 | 0.6129 | 0.0067 | 0.0035 | 0.0007 | 0.0 | 0.0008 | 0.0123 | 0.0 | 0.3235 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.3814 | 0.0 | 0.0099 | 0.0011 | 0.0 | 0.0 | 0.0014 | 0.0036 | 0.0 | 0.0 | 0.5201 | 0.1173 | 0.2045 | 0.0 | 0.0 | 0.0011 | 0.0 |
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+ | 2.5539 | 0.1 | 40 | 2.4846 | 0.0922 | 0.1406 | 0.6363 | nan | 0.6139 | 0.8851 | 0.0 | 0.0001 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.7404 | 0.0 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.7823 | 0.0 | 0.0095 | 0.0001 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.9250 | 0.0450 | 0.3566 | 0.0 | 0.0 | 0.0002 | 0.0 | nan | 0.3914 | 0.6639 | 0.0 | 0.0001 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.4531 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.4448 | 0.0 | 0.0093 | 0.0001 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.6167 | 0.0431 | 0.3282 | 0.0 | 0.0 | 0.0002 | 0.0 |
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+ | 2.1941 | 0.15 | 60 | 2.0471 | 0.1050 | 0.1507 | 0.6598 | nan | 0.6534 | 0.9013 | 0.0 | 0.0000 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.8191 | 0.0 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.8068 | 0.0 | 0.0027 | 0.0 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.9374 | 0.0319 | 0.5185 | 0.0 | 0.0 | 0.0000 | 0.0 | nan | 0.4189 | 0.6905 | 0.0 | 0.0000 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.5057 | 0.0 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.4936 | 0.0 | 0.0027 | 0.0 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.6186 | 0.0311 | 0.4939 | 0.0 | 0.0 | 0.0000 | 0.0 |
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+ | 2.0689 | 0.2 | 80 | 1.8596 | 0.1144 | 0.1599 | 0.6742 | nan | 0.6956 | 0.8961 | 0.0 | 0.0 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.8106 | 0.0 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.8269 | 0.0 | 0.0010 | 0.0 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.9406 | 0.1659 | 0.6189 | 0.0 | 0.0 | 0.0 | 0.0 | nan | 0.4425 | 0.6991 | 0.0 | 0.0 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.5351 | 0.0 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.5100 | 0.0 | 0.0010 | 0.0 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.6370 | 0.1547 | 0.5682 | 0.0 | 0.0 | 0.0 | 0.0 |
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+ | 2.1181 | 0.25 | 100 | 1.6938 | 0.1148 | 0.1605 | 0.6782 | nan | 0.6755 | 0.9120 | 0.0 | 0.0000 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.8326 | 0.0 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.8362 | 0.0 | 0.0004 | 0.0 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.9375 | 0.0969 | 0.6848 | 0.0 | 0.0 | 0.0 | 0.0 | nan | 0.4698 | 0.6984 | 0.0 | 0.0000 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.5419 | 0.0 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.5172 | 0.0 | 0.0004 | 0.0 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.6223 | 0.0891 | 0.6195 | 0.0 | 0.0 | 0.0 | 0.0 |
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+ | 1.7511 | 0.3 | 120 | 1.7105 | 0.1289 | 0.1785 | 0.6857 | nan | 0.7919 | 0.8523 | 0.0 | 0.0 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.9031 | 0.0 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.7983 | 0.0 | 0.0001 | 0.0 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.8947 | 0.4820 | 0.8097 | 0.0 | 0.0 | 0.0 | 0.0 | nan | 0.4352 | 0.7026 | 0.0 | 0.0 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.4821 | 0.0 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.5383 | 0.0 | 0.0001 | 0.0 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.7010 | 0.4272 | 0.7081 | 0.0 | 0.0 | 0.0 | 0.0 |
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+ | 1.6833 | 0.35 | 140 | 1.5535 | 0.1359 | 0.1810 | 0.7089 | nan | 0.7051 | 0.9316 | 0.0 | 0.0001 | 0.0001 | nan | 0.0 | 0.0 | 0.0 | 0.8416 | 0.0 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.8372 | 0.0 | 0.0000 | 0.0 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.9141 | 0.5586 | 0.8235 | 0.0 | 0.0 | 0.0 | 0.0 | nan | 0.4813 | 0.7152 | 0.0 | 0.0001 | 0.0001 | nan | 0.0 | 0.0 | 0.0 | 0.5654 | 0.0 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.5267 | 0.0 | 0.0000 | 0.0 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.7200 | 0.4968 | 0.7074 | 0.0 | 0.0 | 0.0 | 0.0 |
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+ | 1.3625 | 0.4 | 160 | 1.5401 | 0.1379 | 0.1875 | 0.6960 | nan | 0.8227 | 0.8315 | 0.0 | 0.0088 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.8202 | 0.0 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.7865 | 0.0 | 0.0003 | 0.0 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.9384 | 0.7172 | 0.8861 | 0.0 | 0.0 | 0.0 | 0.0 | nan | 0.4355 | 0.6978 | 0.0 | 0.0087 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.5993 | 0.0 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.5463 | 0.0 | 0.0003 | 0.0 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.7186 | 0.5697 | 0.6994 | 0.0 | 0.0 | 0.0 | 0.0 |
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+ | 1.5652 | 0.45 | 180 | 1.4347 | 0.1410 | 0.1858 | 0.7167 | nan | 0.7172 | 0.9289 | 0.0 | 0.0297 | 0.0001 | nan | 0.0 | 0.0 | 0.0 | 0.8140 | 0.0 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.8634 | 0.0 | 0.0 | 0.0 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.9192 | 0.6085 | 0.8794 | 0.0 | 0.0 | 0.0 | 0.0 | nan | 0.4974 | 0.7238 | 0.0 | 0.0297 | 0.0001 | nan | 0.0 | 0.0 | 0.0 | 0.5906 | 0.0 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.5262 | 0.0 | 0.0 | 0.0 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.7211 | 0.5269 | 0.7543 | 0.0 | 0.0 | 0.0 | 0.0 |
134
+ | 2.251 | 0.5 | 200 | 1.3852 | 0.1438 | 0.1954 | 0.7167 | nan | 0.8140 | 0.8843 | 0.0 | 0.0396 | 0.0000 | nan | 0.0 | 0.0 | 0.0 | 0.8636 | 0.0 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.8323 | 0.0 | 0.0002 | 0.0 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.8637 | 0.8718 | 0.8885 | 0.0 | 0.0 | 0.0 | 0.0 | nan | 0.4719 | 0.7384 | 0.0 | 0.0396 | 0.0000 | nan | 0.0 | 0.0 | 0.0 | 0.5543 | 0.0 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.5495 | 0.0 | 0.0002 | 0.0 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.7409 | 0.6157 | 0.7470 | 0.0 | 0.0 | 0.0 | 0.0 |
135
+ | 1.5334 | 0.55 | 220 | 1.3557 | 0.1485 | 0.1958 | 0.7332 | nan | 0.8039 | 0.9151 | 0.0 | 0.0808 | 0.0010 | nan | 0.0 | 0.0 | 0.0 | 0.8567 | 0.0 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.8422 | 0.0 | 0.0001 | 0.0 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.9310 | 0.7820 | 0.8578 | 0.0 | 0.0 | 0.0 | 0.0 | nan | 0.5151 | 0.7568 | 0.0 | 0.0805 | 0.0010 | nan | 0.0 | 0.0 | 0.0 | 0.5778 | 0.0 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.5628 | 0.0 | 0.0001 | 0.0 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.7331 | 0.6244 | 0.7510 | 0.0 | 0.0 | 0.0 | 0.0 |
136
+ | 1.1032 | 0.6 | 240 | 1.3035 | 0.1484 | 0.1983 | 0.7294 | nan | 0.8280 | 0.8915 | 0.0 | 0.0295 | 0.0006 | nan | 0.0 | 0.0 | 0.0 | 0.8420 | 0.0 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.8958 | 0.0 | 0.0000 | 0.0 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.8890 | 0.8915 | 0.8781 | 0.0 | 0.0 | 0.0 | 0.0 | nan | 0.5051 | 0.7588 | 0.0 | 0.0295 | 0.0006 | nan | 0.0 | 0.0 | 0.0 | 0.5893 | 0.0 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.5361 | 0.0 | 0.0000 | 0.0 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.7585 | 0.6389 | 0.7831 | 0.0 | 0.0 | 0.0 | 0.0 |
137
+ | 1.5162 | 0.65 | 260 | 1.2855 | 0.1499 | 0.1982 | 0.7346 | nan | 0.7899 | 0.9274 | 0.0 | 0.0696 | 0.0004 | nan | 0.0 | 0.0 | 0.0 | 0.8823 | 0.0 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.7802 | 0.0 | 0.0001 | 0.0 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.9275 | 0.8540 | 0.9115 | 0.0 | 0.0 | 0.0 | 0.0 | nan | 0.5089 | 0.7497 | 0.0 | 0.0693 | 0.0004 | nan | 0.0 | 0.0 | 0.0 | 0.5665 | 0.0 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.5720 | 0.0 | 0.0001 | 0.0 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.7467 | 0.6577 | 0.7756 | 0.0 | 0.0 | 0.0 | 0.0 |
138
+ | 1.423 | 0.7 | 280 | 1.1915 | 0.1506 | 0.1993 | 0.7353 | nan | 0.7402 | 0.9425 | 0.0 | 0.0845 | 0.0010 | nan | 0.0 | 0.0 | 0.0 | 0.8551 | 0.0 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.8733 | 0.0 | 0.0 | 0.0 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.8687 | 0.9102 | 0.9032 | 0.0 | 0.0 | 0.0 | 0.0 | nan | 0.5234 | 0.7414 | 0.0 | 0.0841 | 0.0010 | nan | 0.0 | 0.0 | 0.0 | 0.6108 | 0.0 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.5614 | 0.0 | 0.0 | 0.0 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.7488 | 0.6217 | 0.7766 | 0.0 | 0.0 | 0.0 | 0.0 |
139
+ | 1.5383 | 0.75 | 300 | 1.2519 | 0.1443 | 0.1948 | 0.7075 | nan | 0.8838 | 0.8184 | 0.0 | 0.0051 | 0.0001 | nan | 0.0 | 0.0 | 0.0 | 0.8848 | 0.0 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.7914 | 0.0 | 0.0005 | 0.0 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.9453 | 0.7949 | 0.9133 | 0.0 | 0.0 | 0.0 | 0.0 | nan | 0.4399 | 0.7253 | 0.0 | 0.0051 | 0.0001 | nan | 0.0 | 0.0 | 0.0 | 0.5790 | 0.0 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.5762 | 0.0 | 0.0005 | 0.0 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.7339 | 0.6488 | 0.7635 | 0.0 | 0.0 | 0.0 | 0.0 |
140
+ | 1.1151 | 0.8 | 320 | 1.1587 | 0.1554 | 0.2030 | 0.7440 | nan | 0.7824 | 0.9307 | 0.0 | 0.1656 | 0.0020 | nan | 0.0 | 0.0 | 0.0 | 0.8517 | 0.0 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.8978 | 0.0 | 0.0 | 0.0 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.8867 | 0.9163 | 0.8613 | 0.0 | 0.0 | 0.0 | 0.0 | nan | 0.5322 | 0.7605 | 0.0 | 0.1648 | 0.0020 | nan | 0.0 | 0.0 | 0.0 | 0.6094 | 0.0 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.5644 | 0.0 | 0.0 | 0.0 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.7635 | 0.6291 | 0.7922 | 0.0 | 0.0 | 0.0 | 0.0 |
141
+ | 1.8368 | 0.85 | 340 | 1.1384 | 0.1576 | 0.2078 | 0.7473 | nan | 0.7884 | 0.9303 | 0.0 | 0.2963 | 0.0030 | nan | 0.0 | 0.0 | 0.0 | 0.8826 | 0.0 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.8052 | 0.0 | 0.0001 | 0.0 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.9000 | 0.9177 | 0.9172 | 0.0 | 0.0 | 0.0 | 0.0 | nan | 0.5405 | 0.7619 | 0.0 | 0.2939 | 0.0030 | nan | 0.0 | 0.0 | 0.0 | 0.5768 | 0.0 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.5739 | 0.0 | 0.0001 | 0.0 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.7456 | 0.6228 | 0.7663 | 0.0 | 0.0 | 0.0 | 0.0 |
142
+ | 1.0473 | 0.9 | 360 | 1.1197 | 0.1620 | 0.2067 | 0.7529 | nan | 0.8541 | 0.9158 | 0.0 | 0.2833 | 0.0019 | nan | 0.0 | 0.0 | 0.0 | 0.8277 | 0.0 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.8720 | 0.0 | 0.0010 | 0.0 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.9178 | 0.8401 | 0.8938 | 0.0 | 0.0 | 0.0 | 0.0 | nan | 0.5348 | 0.7771 | 0.0 | 0.2824 | 0.0019 | nan | 0.0 | 0.0 | 0.0 | 0.6333 | 0.0 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.5658 | 0.0 | 0.0010 | 0.0 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.7679 | 0.6838 | 0.7734 | 0.0 | 0.0 | 0.0 | 0.0 |
143
+ | 1.2099 | 0.95 | 380 | 1.1402 | 0.1596 | 0.2125 | 0.7489 | nan | 0.8279 | 0.9097 | 0.0 | 0.3973 | 0.0049 | nan | 0.0 | 0.0 | 0.0 | 0.8926 | 0.0 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.8234 | 0.0 | 0.0045 | 0.0 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.8687 | 0.9479 | 0.9095 | 0.0 | 0.0 | 0.0 | 0.0 | nan | 0.5527 | 0.7692 | 0.0 | 0.3760 | 0.0048 | nan | 0.0 | 0.0 | 0.0 | 0.5899 | 0.0 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.5926 | 0.0 | 0.0045 | 0.0 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.7353 | 0.5382 | 0.7842 | 0.0 | 0.0 | 0.0 | 0.0 |
144
+ | 1.4778 | 1.0 | 400 | 1.0639 | 0.1629 | 0.2062 | 0.7559 | nan | 0.7707 | 0.9485 | 0.0 | 0.3733 | 0.0050 | nan | 0.0 | 0.0 | 0.0 | 0.8102 | 0.0 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.8614 | 0.0 | 0.0006 | 0.0 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.9319 | 0.7720 | 0.9201 | 0.0 | 0.0 | 0.0 | 0.0 | nan | 0.5704 | 0.7620 | 0.0 | 0.3430 | 0.0050 | nan | 0.0 | 0.0 | 0.0 | 0.6244 | 0.0 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.5635 | 0.0 | 0.0006 | 0.0 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.7570 | 0.6502 | 0.7751 | 0.0 | 0.0 | 0.0 | 0.0 |
145
+ | 1.3524 | 1.05 | 420 | 1.0537 | 0.1646 | 0.2128 | 0.7594 | nan | 0.8552 | 0.9147 | 0.0 | 0.3862 | 0.0047 | nan | 0.0000 | 0.0 | 0.0 | 0.8886 | 0.0 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.8363 | 0.0 | 0.0012 | 0.0 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.9223 | 0.8621 | 0.9254 | 0.0 | 0.0 | 0.0 | 0.0 | nan | 0.5567 | 0.7816 | 0.0 | 0.3792 | 0.0047 | nan | 0.0000 | 0.0 | 0.0 | 0.5949 | 0.0 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.5790 | 0.0 | 0.0011 | 0.0 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.7683 | 0.6633 | 0.7752 | 0.0 | 0.0 | 0.0 | 0.0 |
146
+ | 1.13 | 1.1 | 440 | 1.0641 | 0.1623 | 0.2100 | 0.7552 | nan | 0.8688 | 0.9058 | 0.0 | 0.3920 | 0.0061 | nan | 0.0001 | 0.0 | 0.0 | 0.8676 | 0.0 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.7887 | 0.0 | 0.0043 | 0.0 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.9566 | 0.8035 | 0.9177 | 0.0 | 0.0 | 0.0 | 0.0 | nan | 0.5569 | 0.7839 | 0.0 | 0.3826 | 0.0060 | nan | 0.0001 | 0.0 | 0.0 | 0.6087 | 0.0 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.5866 | 0.0 | 0.0042 | 0.0 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.7200 | 0.6085 | 0.7728 | 0.0 | 0.0 | 0.0 | 0.0 |
147
+ | 0.9163 | 1.15 | 460 | 1.0375 | 0.1669 | 0.2122 | 0.7625 | nan | 0.7922 | 0.9441 | 0.0 | 0.4037 | 0.0117 | nan | 0.0 | 0.0 | 0.0 | 0.8629 | 0.0 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.8731 | 0.0 | 0.0161 | 0.0 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.9124 | 0.8587 | 0.9033 | 0.0 | 0.0 | 0.0 | 0.0 | nan | 0.5745 | 0.7713 | 0.0 | 0.3669 | 0.0115 | nan | 0.0 | 0.0 | 0.0 | 0.6337 | 0.0 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.5842 | 0.0 | 0.0160 | 0.0 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.7742 | 0.6522 | 0.7883 | 0.0 | 0.0 | 0.0 | 0.0 |
148
+ | 0.9166 | 1.2 | 480 | 1.0155 | 0.1683 | 0.2160 | 0.7657 | nan | 0.8269 | 0.9353 | 0.0 | 0.4213 | 0.0204 | nan | 0.0001 | 0.0 | 0.0 | 0.8988 | 0.0 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.8703 | 0.0 | 0.0283 | 0.0 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.8959 | 0.8917 | 0.9064 | 0.0 | 0.0 | 0.0 | 0.0 | nan | 0.5802 | 0.7839 | 0.0 | 0.3953 | 0.0197 | nan | 0.0001 | 0.0 | 0.0 | 0.6081 | 0.0 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.5865 | 0.0 | 0.0278 | 0.0 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.7779 | 0.6530 | 0.7844 | 0.0 | 0.0 | 0.0 | 0.0 |
149
+ | 1.1753 | 1.25 | 500 | 1.0090 | 0.1691 | 0.2150 | 0.7662 | nan | 0.7755 | 0.9463 | 0.0 | 0.4466 | 0.0306 | nan | 0.0012 | 0.0 | 0.0 | 0.8801 | 0.0 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.8743 | 0.0 | 0.0047 | 0.0 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.9204 | 0.8869 | 0.8998 | 0.0 | 0.0 | 0.0 | 0.0 | nan | 0.5951 | 0.7715 | 0.0 | 0.4037 | 0.0296 | nan | 0.0012 | 0.0 | 0.0 | 0.6267 | 0.0 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.5790 | 0.0 | 0.0047 | 0.0 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.7733 | 0.6728 | 0.7853 | 0.0 | 0.0 | 0.0 | 0.0 |
150
+ | 1.0271 | 1.3 | 520 | 1.0026 | 0.1693 | 0.2156 | 0.7668 | nan | 0.8177 | 0.9396 | 0.0 | 0.4255 | 0.0255 | nan | 0.0004 | 0.0 | 0.0 | 0.8799 | 0.0 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.8736 | 0.0 | 0.0105 | 0.0 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.9017 | 0.8936 | 0.9169 | 0.0 | 0.0 | 0.0 | 0.0 | nan | 0.5912 | 0.7772 | 0.0 | 0.4068 | 0.0247 | nan | 0.0004 | 0.0 | 0.0 | 0.6212 | 0.0 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.5754 | 0.0 | 0.0104 | 0.0 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.7784 | 0.6832 | 0.7782 | 0.0 | 0.0 | 0.0 | 0.0 |
151
+ | 1.1564 | 1.35 | 540 | 0.9947 | 0.1696 | 0.2148 | 0.7660 | nan | 0.7851 | 0.9423 | 0.0 | 0.4547 | 0.0382 | nan | 0.0004 | 0.0 | 0.0 | 0.8674 | 0.0 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.8639 | 0.0 | 0.0128 | 0.0 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.9343 | 0.8540 | 0.9054 | 0.0 | 0.0 | 0.0 | 0.0 | nan | 0.5956 | 0.7720 | 0.0 | 0.4192 | 0.0359 | nan | 0.0004 | 0.0 | 0.0 | 0.6274 | 0.0 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.5781 | 0.0 | 0.0127 | 0.0 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.7658 | 0.6675 | 0.7816 | 0.0 | 0.0 | 0.0 | 0.0 |
152
+ | 0.8783 | 1.4 | 560 | 0.9893 | 0.1700 | 0.2180 | 0.7636 | nan | 0.8414 | 0.9153 | 0.0 | 0.4471 | 0.0536 | nan | 0.0001 | 0.0 | 0.0 | 0.8736 | 0.0 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.8714 | 0.0 | 0.0164 | 0.0 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.9007 | 0.9204 | 0.9170 | 0.0 | 0.0 | 0.0 | 0.0 | nan | 0.5617 | 0.7824 | 0.0 | 0.4156 | 0.0496 | nan | 0.0001 | 0.0 | 0.0 | 0.6400 | 0.0 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.5854 | 0.0 | 0.0163 | 0.0 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.7741 | 0.6553 | 0.7882 | 0.0 | 0.0 | 0.0 | 0.0 |
153
+ | 1.282 | 1.45 | 580 | 0.9758 | 0.1717 | 0.2182 | 0.7692 | nan | 0.8157 | 0.9327 | 0.0 | 0.4624 | 0.0695 | nan | 0.0011 | 0.0 | 0.0 | 0.8994 | 0.0 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.8471 | 0.0 | 0.0319 | 0.0 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.9419 | 0.8405 | 0.9216 | 0.0 | 0.0 | 0.0 | 0.0 | nan | 0.5872 | 0.7850 | 0.0 | 0.4214 | 0.0620 | nan | 0.0011 | 0.0 | 0.0 | 0.6214 | 0.0 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.6052 | 0.0 | 0.0316 | 0.0 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.7636 | 0.6415 | 0.8024 | 0.0 | 0.0 | 0.0 | 0.0 |
154
+ | 2.0178 | 1.5 | 600 | 0.9683 | 0.1726 | 0.2195 | 0.7706 | nan | 0.8139 | 0.9362 | 0.0 | 0.4811 | 0.0607 | nan | 0.0021 | 0.0 | 0.0 | 0.8846 | 0.0 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.8490 | 0.0 | 0.0508 | 0.0 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.9324 | 0.8641 | 0.9310 | 0.0 | 0.0 | 0.0 | 0.0 | nan | 0.5911 | 0.7843 | 0.0 | 0.4197 | 0.0553 | nan | 0.0021 | 0.0 | 0.0 | 0.6375 | 0.0 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.6044 | 0.0 | 0.0505 | 0.0 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.7732 | 0.6395 | 0.7940 | 0.0 | 0.0 | 0.0 | 0.0 |
155
+ | 0.9306 | 1.55 | 620 | 0.9687 | 0.1727 | 0.2200 | 0.7706 | nan | 0.8171 | 0.9378 | 0.0 | 0.4601 | 0.0567 | nan | 0.0022 | 0.0 | 0.0 | 0.9099 | 0.0 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.8513 | 0.0 | 0.0563 | 0.0 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.9183 | 0.8808 | 0.9294 | 0.0 | 0.0 | 0.0 | 0.0 | nan | 0.5877 | 0.7853 | 0.0 | 0.4123 | 0.0518 | nan | 0.0022 | 0.0 | 0.0 | 0.6194 | 0.0 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.5984 | 0.0 | 0.0555 | 0.0 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.7828 | 0.6705 | 0.7895 | 0.0 | 0.0 | 0.0 | 0.0 |
156
+ | 1.1456 | 1.6 | 640 | 0.9496 | 0.1728 | 0.2190 | 0.7704 | nan | 0.8418 | 0.9310 | 0.0 | 0.4376 | 0.0602 | nan | 0.0044 | 0.0 | 0.0 | 0.8726 | 0.0 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.8843 | 0.0 | 0.0329 | 0.0 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.9063 | 0.8883 | 0.9307 | 0.0 | 0.0 | 0.0 | 0.0 | nan | 0.5862 | 0.7886 | 0.0 | 0.4105 | 0.0552 | nan | 0.0044 | 0.0 | 0.0 | 0.6434 | 0.0 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.5812 | 0.0 | 0.0324 | 0.0 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.7896 | 0.6753 | 0.7900 | 0.0 | 0.0 | 0.0 | 0.0 |
157
+ | 1.2237 | 1.65 | 660 | 0.9564 | 0.1712 | 0.2206 | 0.7665 | nan | 0.8216 | 0.9244 | 0.0 | 0.4856 | 0.0672 | nan | 0.0074 | 0.0 | 0.0 | 0.8700 | 0.0 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.8779 | 0.0 | 0.0291 | 0.0 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.8889 | 0.9380 | 0.9269 | 0.0 | 0.0 | 0.0 | 0.0 | nan | 0.5866 | 0.7847 | 0.0 | 0.4095 | 0.0602 | nan | 0.0074 | 0.0 | 0.0 | 0.6498 | 0.0 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.5852 | 0.0 | 0.0287 | 0.0 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.7783 | 0.6227 | 0.7932 | 0.0 | 0.0 | 0.0 | 0.0 |
158
+ | 1.14 | 1.7 | 680 | 0.9590 | 0.1717 | 0.2212 | 0.7676 | nan | 0.8358 | 0.9203 | 0.0 | 0.4628 | 0.0661 | nan | 0.0141 | 0.0 | 0.0 | 0.8984 | 0.0 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.8603 | 0.0 | 0.0397 | 0.0 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.9056 | 0.9322 | 0.9227 | 0.0 | 0.0 | 0.0 | 0.0 | nan | 0.5852 | 0.7859 | 0.0 | 0.4126 | 0.0597 | nan | 0.0139 | 0.0 | 0.0 | 0.6233 | 0.0 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.5932 | 0.0 | 0.0390 | 0.0 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.7793 | 0.6376 | 0.7923 | 0.0 | 0.0 | 0.0 | 0.0 |
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+ | 0.8264 | 1.75 | 700 | 0.9440 | 0.1736 | 0.2211 | 0.7704 | nan | 0.8423 | 0.9270 | 0.0 | 0.4383 | 0.0661 | nan | 0.0119 | 0.0 | 0.0 | 0.8952 | 0.0 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.8535 | 0.0 | 0.0634 | 0.0000 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.9183 | 0.9149 | 0.9229 | 0.0 | 0.0 | 0.0 | 0.0 | nan | 0.5849 | 0.7866 | 0.0 | 0.4085 | 0.0596 | nan | 0.0118 | 0.0 | 0.0 | 0.6285 | 0.0 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.6006 | 0.0 | 0.0625 | 0.0000 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.7804 | 0.6604 | 0.7970 | 0.0 | 0.0 | 0.0 | 0.0 |
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+ | 1.533 | 1.8 | 720 | 0.9434 | 0.1735 | 0.2211 | 0.7691 | nan | 0.8450 | 0.9235 | 0.0 | 0.4450 | 0.0624 | nan | 0.0092 | 0.0 | 0.0 | 0.8964 | 0.0 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.8572 | 0.0 | 0.0659 | 0.0000 | 0.0 | nan | 0.0 | 0.0000 | 0.0 | 0.0 | 0.9106 | 0.9100 | 0.9305 | 0.0 | 0.0 | 0.0 | 0.0 | nan | 0.5785 | 0.7831 | 0.0 | 0.4092 | 0.0567 | nan | 0.0091 | 0.0 | 0.0 | 0.6284 | 0.0 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.5997 | 0.0 | 0.0649 | 0.0000 | 0.0 | nan | 0.0 | 0.0000 | 0.0 | 0.0 | 0.7861 | 0.6699 | 0.7942 | 0.0 | 0.0 | 0.0 | 0.0 |
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+ | 1.4749 | 1.85 | 740 | 0.9403 | 0.1742 | 0.2195 | 0.7712 | nan | 0.8383 | 0.9330 | 0.0 | 0.4287 | 0.0651 | nan | 0.0085 | 0.0 | 0.0 | 0.8793 | 0.0 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.8680 | 0.0 | 0.0522 | 0.0000 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.9213 | 0.8967 | 0.9120 | 0.0 | 0.0 | 0.0 | 0.0 | nan | 0.5856 | 0.7830 | 0.0 | 0.4053 | 0.0589 | nan | 0.0084 | 0.0 | 0.0 | 0.6463 | 0.0 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.5982 | 0.0 | 0.0515 | 0.0000 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.7840 | 0.6829 | 0.7962 | 0.0 | 0.0 | 0.0 | 0.0 |
162
+ | 0.7973 | 1.9 | 760 | 0.9333 | 0.1739 | 0.2203 | 0.7708 | nan | 0.8428 | 0.9280 | 0.0 | 0.4393 | 0.0688 | nan | 0.0111 | 0.0 | 0.0 | 0.8836 | 0.0 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.8722 | 0.0 | 0.0422 | 0.0000 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.9143 | 0.9051 | 0.9208 | 0.0 | 0.0 | 0.0 | 0.0 | nan | 0.5849 | 0.7849 | 0.0 | 0.4095 | 0.0621 | nan | 0.0109 | 0.0 | 0.0 | 0.6428 | 0.0 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.5950 | 0.0 | 0.0416 | 0.0000 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.7877 | 0.6738 | 0.7970 | 0.0 | 0.0 | 0.0 | 0.0 |
163
+ | 0.8955 | 1.95 | 780 | 0.9455 | 0.1741 | 0.2208 | 0.7719 | nan | 0.8240 | 0.9347 | 0.0 | 0.4616 | 0.0726 | nan | 0.0138 | 0.0 | 0.0 | 0.8819 | 0.0 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.8736 | 0.0 | 0.0362 | 0.0 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.9138 | 0.9057 | 0.9261 | 0.0 | 0.0 | 0.0 | 0.0 | nan | 0.5964 | 0.7838 | 0.0 | 0.4196 | 0.0651 | nan | 0.0137 | 0.0 | 0.0 | 0.6425 | 0.0 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.5920 | 0.0 | 0.0357 | 0.0 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.7871 | 0.6654 | 0.7968 | 0.0 | 0.0 | 0.0 | 0.0 |
164
+ | 1.0652 | 2.0 | 800 | 0.9415 | 0.1739 | 0.2202 | 0.7714 | nan | 0.8361 | 0.9327 | 0.0 | 0.4491 | 0.0618 | nan | 0.0106 | 0.0 | 0.0 | 0.8757 | 0.0 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.8775 | 0.0 | 0.0398 | 0.0000 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.9075 | 0.9080 | 0.9280 | 0.0 | 0.0 | 0.0 | 0.0 | nan | 0.5895 | 0.7842 | 0.0 | 0.4140 | 0.0569 | nan | 0.0105 | 0.0 | 0.0 | 0.6473 | 0.0 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.5914 | 0.0 | 0.0393 | 0.0000 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.7895 | 0.6699 | 0.7975 | 0.0 | 0.0 | 0.0 | 0.0 |
165
+
166
+
167
+ ### Framework versions
168
+
169
+ - Transformers 4.44.2
170
+ - Pytorch 2.4.1+cu121
171
+ - Datasets 3.0.1
172
+ - Tokenizers 0.19.1
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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