File size: 1,909 Bytes
3ece011 7fd6a70 3ece011 fd038e0 3ece011 fd038e0 3ece011 7fd6a70 3ece011 fd038e0 3ece011 fd038e0 3ece011 fd038e0 3ece011 7fd6a70 3ece011 a099436 3ece011 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 |
---
license: apache-2.0
tags:
- text-classification
- generated_from_trainer
datasets:
- glue
metrics:
- accuracy
- f1
base_model: distilroberta-base
model-index:
- name: platzi-distilroberta-base-mrpc-glue-luigitercero
results:
- task:
type: text-classification
name: Text Classification
dataset:
name: datasetX
type: glue
config: mrpc
split: validation
args: mrpc
metrics:
- type: accuracy
value: 0.8431372549019608
name: Accuracy
- type: f1
value: 0.8836363636363636
name: F1
---
<!-- 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. -->
# platzi-distilroberta-base-mrpc-glue-luigitercero
This model is a fine-tuned version of [distilroberta-base](https://huggingface.co/distilroberta-base) on the datasetX dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6591
- Accuracy: 0.8431
- F1: 0.8836
## 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: 5e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
| 0.1853 | 1.09 | 500 | 0.6591 | 0.8431 | 0.8836 |
| 0.1812 | 2.18 | 1000 | 0.6591 | 0.8431 | 0.8836 |
### Framework versions
- Transformers 4.26.1
- Pytorch 1.13.1+cu116
- Datasets 2.9.0
- Tokenizers 0.13.2
|