pytorch tensorboard gpt2 token-classification transformers generated_from_trainer license:mit model-index autotrain_compatible
---
license: mit
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: gpt2-finetuned-comp2
  results: []
---

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# gpt2-finetuned-comp2

This model is a fine-tuned version of [gpt2](https://huggingface.co/gpt2) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.7788
- Precision: 0.3801
- Recall: 0.6854
- F1: 0.4800
- Accuracy: 0.4800

## 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: 1
- eval_batch_size: 1
- seed: 42
- gradient_accumulation_steps: 8
- total_train_batch_size: 8
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 7

### Training results

| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| 1.0962        | 1.0   | 1012 | 0.7528          | 0.3793    | 0.6109 | 0.4411 | 0.4411   |
| 0.7022        | 2.0   | 2024 | 0.6763          | 0.3992    | 0.6557 | 0.4799 | 0.4799   |
| 0.6136        | 3.0   | 3036 | 0.6751          | 0.3995    | 0.6597 | 0.4824 | 0.4824   |
| 0.5444        | 4.0   | 4048 | 0.6799          | 0.3891    | 0.6817 | 0.4854 | 0.4854   |
| 0.4846        | 5.0   | 5060 | 0.7371          | 0.4030    | 0.6701 | 0.4906 | 0.4906   |
| 0.4379        | 6.0   | 6072 | 0.7520          | 0.3956    | 0.6788 | 0.4887 | 0.4887   |
| 0.404         | 7.0   | 7084 | 0.7788          | 0.3801    | 0.6854 | 0.4800 | 0.4800   |


### Framework versions

- Transformers 4.17.0
- Pytorch 1.10.0+cu111
- Datasets 2.0.0
- Tokenizers 0.11.6
