aai520-group6
/

roberta-finetuned-squad_v2

@@ -1,235 +1,68 @@
 ---
-language: en
-license: mit
 model-index:
-- name: roberta-finetuned
-  results:
-  - task:
-      type: question-answering
-    dataset:
-      name: SQuAD v2
-      type: squad_v2
-    metrics:
-    - type: Exact
-      value: 37.40419439063421
-    - type: F1
-      value: 40.42817816263742
-    - type: Total
-      value: 11873
-    - type: Hasans Exact
-      value: 72.58771929824562
-    - type: Hasans F1
-      value: 78.64435886049151
-    - type: Hasans Total
-      value: 5928
-    - type: Noans Exact
-      value: 2.3212783851976453
-    - type: Noans F1
-      value: 2.3212783851976453
-    - type: Noans Total
-      value: 5945
-    - type: Best Exact
-      value: 50.09685841825992
-    - type: Best Exact Thresh
-      value: 0.0
-    - type: Best F1
-      value: 50.09685841825992
-    - type: Best F1 Thresh
-      value: 0.0
 ---
-# Model Card for Model ID
-<!-- Provide a quick summary of what the model is/does. -->
-## Model Details
-### Model Description
-<!-- Provide a longer summary of what this model is. -->
-- **Developed by:** [More Information Needed]
-- **Shared by [optional]:** [More Information Needed]
-- **Model type:** [More Information Needed]
-- **Language(s) (NLP):** en
-- **License:** mit
-- **Finetuned from model [optional]:** [More Information Needed]
-### Model Sources [optional]
-<!-- Provide the basic links for the model. -->
-- **Repository:** [More Information Needed]
-- **Paper [optional]:** [More Information Needed]
-- **Demo [optional]:** [More Information Needed]
-## Uses
-<!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
-### Direct Use
-<!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
-[More Information Needed]
-### Downstream Use [optional]
-<!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
-[More Information Needed]
-### Out-of-Scope Use
-<!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
-[More Information Needed]
-## Bias, Risks, and Limitations
-<!-- This section is meant to convey both technical and sociotechnical limitations. -->
-[More Information Needed]
-### Recommendations
-<!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
-Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
-## How to Get Started with the Model
-Use the code below to get started with the model.
-[More Information Needed]
-## Training Details
-### Training Data
-<!-- This should link to a Data Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. -->
-[More Information Needed]
-### Training Procedure
-<!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->
-#### Preprocessing [optional]
-[More Information Needed]
-#### Training Hyperparameters
-- **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
-#### Speeds, Sizes, Times [optional]
-<!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
-[More Information Needed]
-## Evaluation
-<!-- This section describes the evaluation protocols and provides the results. -->
-### Testing Data, Factors & Metrics
-#### Testing Data
-<!-- This should link to a Data Card if possible. -->
-[More Information Needed]
-#### Factors
-<!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
-[More Information Needed]
-#### Metrics
-<!-- These are the evaluation metrics being used, ideally with a description of why. -->
-[More Information Needed]
-### Results
-[More Information Needed]
-#### Summary
-## Model Examination [optional]
-<!-- Relevant interpretability work for the model goes here -->
-[More Information Needed]
-## Environmental Impact
-<!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
-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).
-- **Hardware Type:** [More Information Needed]
-- **Hours used:** [More Information Needed]
-- **Cloud Provider:** [More Information Needed]
-- **Compute Region:** [More Information Needed]
-- **Carbon Emitted:** [More Information Needed]
-## Technical Specifications [optional]
-### Model Architecture and Objective
-[More Information Needed]
-### Compute Infrastructure
-[More Information Needed]
-#### Hardware
-[More Information Needed]
-#### Software
-[More Information Needed]
-## Citation [optional]
-<!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
-**BibTeX:**
-[More Information Needed]
-**APA:**
-[More Information Needed]
-## Glossary [optional]
-<!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. -->
-[More Information Needed]
-## More Information [optional]
-[More Information Needed]
-## Model Card Authors [optional]
-[More Information Needed]
-## Model Card Contact
-[More Information Needed]

 ---
+tags:
+- generated_from_trainer
+datasets:
+- squad_v2
 model-index:
+- name: roberta-finetuned-squad_v2
+  results: []
 ---
+<!-- This model card has been generated automatically according to the information the Trainer had access to. You
+should probably proofread and complete it, then remove this comment. -->
+# roberta-finetuned-squad_v2
+This model was trained from scratch on the squad_v2 dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.9064
+## Model description
+More information needed
+## Intended uses & limitations
+More information needed
+## Training and evaluation data
+More information needed
+## Training procedure
+### Training hyperparameters
+The following hyperparameters were used during training:
+- learning_rate: 2e-05
+- train_batch_size: 256
+- eval_batch_size: 256
+- seed: 42
+- gradient_accumulation_steps: 4
+- total_train_batch_size: 1024
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- num_epochs: 4
+### Training results
+| Training Loss | Epoch | Step | Validation Loss |
+|:-------------:|:-----:|:----:|:---------------:|
+| 2.9129        | 0.2   | 100  | 1.4700          |
+| 1.4395        | 0.39  | 200  | 1.2407          |
+| 1.2356        | 0.59  | 300  | 1.0325          |
+| 1.1284        | 0.78  | 400  | 0.9750          |
+| 1.0821        | 0.98  | 500  | 0.9345          |
+| 0.9978        | 1.18  | 600  | 0.9893          |
+| 0.9697        | 1.37  | 700  | 0.9300          |
+| 0.9455        | 1.57  | 800  | 0.9351          |
+| 0.9322        | 1.76  | 900  | 0.9451          |
+| 0.9269        | 1.96  | 1000 | 0.9064          |
+### Framework versions
+- Transformers 4.34.1
+- Pytorch 2.1.0+cu118
+- Datasets 2.14.5
+- Tokenizers 0.14.1

trainer_state.json CHANGED Viewed

@@ -153,16 +153,16 @@
       "step": 1000,
       "total_flos": 6.688961805360538e+16,
       "train_loss": 0.0,
-      "train_runtime": 0.5897,
-      "train_samples_per_second": 221400.674,
-      "train_steps_per_second": 432.453
     },
     {
       "epoch": 1.96,
       "eval_loss": 0.9063528180122375,
-      "eval_runtime": 17.3618,
-      "eval_samples_per_second": 688.58,
-      "eval_steps_per_second": 5.414,
       "step": 1000
     }
   ],

       "step": 1000,
       "total_flos": 6.688961805360538e+16,
       "train_loss": 0.0,
+      "train_runtime": 0.614,
+      "train_samples_per_second": 212612.275,
+      "train_steps_per_second": 415.287
     },
     {
       "epoch": 1.96,
       "eval_loss": 0.9063528180122375,
+      "eval_runtime": 17.3907,
+      "eval_samples_per_second": 687.437,
+      "eval_steps_per_second": 5.405,
       "step": 1000
     }
   ],

training_args.bin CHANGED Viewed

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:9c38402081e29ac8ee9e727b8756c0fd6650f5c2f87de20c1e0ce9d11d10ba63
 size 4664

 version https://git-lfs.github.com/spec/v1
+oid sha256:1776a22620d47e79406d32e398cf9107341a37c14af882ed10b1cef99f96d914
 size 4664