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--- |
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license: mit |
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tags: |
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- generated_from_trainer |
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metrics: |
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- precision |
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- recall |
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- f1 |
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- accuracy |
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model-index: |
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- name: GPT2_v5 |
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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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# GPT2_v5 |
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This model is a fine-tuned version of [gpt2](https://huggingface.co/gpt2) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.7670 |
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- Precision: 0.7725 |
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- Recall: 0.8367 |
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- F1: 0.4733 |
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- Accuracy: 0.7646 |
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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: 5e-05 |
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- train_batch_size: 1 |
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- eval_batch_size: 1 |
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- seed: 42 |
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- gradient_accumulation_steps: 8 |
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- total_train_batch_size: 8 |
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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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- lr_scheduler_warmup_ratio: 0.1 |
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- num_epochs: 7 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy | |
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|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:| |
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| 1.2212 | 1.0 | 1012 | 0.7874 | 0.7557 | 0.7560 | 0.4041 | 0.7150 | |
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| 0.7162 | 2.0 | 2024 | 0.7007 | 0.7495 | 0.8714 | 0.4855 | 0.7647 | |
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| 0.6241 | 3.0 | 3036 | 0.6799 | 0.7681 | 0.8532 | 0.4804 | 0.7702 | |
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| 0.5545 | 4.0 | 4048 | 0.6997 | 0.7635 | 0.8658 | 0.4814 | 0.7714 | |
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| 0.4963 | 5.0 | 5060 | 0.7186 | 0.7696 | 0.8470 | 0.4764 | 0.7669 | |
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| 0.449 | 6.0 | 6072 | 0.7436 | 0.7711 | 0.8382 | 0.4731 | 0.7644 | |
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| 0.4182 | 7.0 | 7084 | 0.7670 | 0.7725 | 0.8367 | 0.4733 | 0.7646 | |
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### Framework versions |
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- Transformers 4.18.0 |
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- Pytorch 1.10.0+cu111 |
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- Datasets 2.1.0 |
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- Tokenizers 0.12.1 |
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