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--- |
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license: apache-2.0 |
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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: token_fine_tunned_flipkart_2_gl7 |
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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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# token_fine_tunned_flipkart_2_gl7 |
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This model is a fine-tuned version of [vinayak361/token_fine_tunned_flipkart_2_gl](https://huggingface.co/vinayak361/token_fine_tunned_flipkart_2_gl) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.7179 |
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- Precision: 0.7122 |
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- Recall: 0.7571 |
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- F1: 0.7340 |
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- Accuracy: 0.7485 |
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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: 2e-06 |
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- train_batch_size: 16 |
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- eval_batch_size: 16 |
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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: 20 |
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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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| No log | 1.0 | 135 | 1.0392 | 0.6634 | 0.7121 | 0.6869 | 0.6982 | |
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| No log | 2.0 | 270 | 0.8567 | 0.6697 | 0.7128 | 0.6906 | 0.7093 | |
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| No log | 3.0 | 405 | 0.8102 | 0.6707 | 0.7204 | 0.6947 | 0.7146 | |
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| 0.9223 | 4.0 | 540 | 0.7840 | 0.6860 | 0.7363 | 0.7103 | 0.7253 | |
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| 0.9223 | 5.0 | 675 | 0.7668 | 0.6886 | 0.7301 | 0.7088 | 0.7267 | |
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| 0.9223 | 6.0 | 810 | 0.7543 | 0.6886 | 0.7329 | 0.7100 | 0.7301 | |
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| 0.9223 | 7.0 | 945 | 0.7501 | 0.6997 | 0.7384 | 0.7185 | 0.7340 | |
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| 0.708 | 8.0 | 1080 | 0.7383 | 0.6949 | 0.7426 | 0.7180 | 0.7335 | |
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| 0.708 | 9.0 | 1215 | 0.7360 | 0.7030 | 0.7453 | 0.7235 | 0.7379 | |
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| 0.708 | 10.0 | 1350 | 0.7319 | 0.7048 | 0.7453 | 0.7245 | 0.7389 | |
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| 0.708 | 11.0 | 1485 | 0.7306 | 0.7052 | 0.7467 | 0.7254 | 0.7398 | |
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| 0.6327 | 12.0 | 1620 | 0.7220 | 0.7049 | 0.7488 | 0.7262 | 0.7413 | |
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| 0.6327 | 13.0 | 1755 | 0.7198 | 0.7059 | 0.7509 | 0.7277 | 0.7432 | |
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| 0.6327 | 14.0 | 1890 | 0.7203 | 0.7108 | 0.7585 | 0.7338 | 0.7481 | |
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| 0.5954 | 15.0 | 2025 | 0.7193 | 0.7118 | 0.7571 | 0.7337 | 0.7481 | |
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| 0.5954 | 16.0 | 2160 | 0.7175 | 0.7122 | 0.7585 | 0.7346 | 0.7476 | |
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| 0.5954 | 17.0 | 2295 | 0.7176 | 0.7144 | 0.7599 | 0.7364 | 0.7481 | |
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| 0.5954 | 18.0 | 2430 | 0.7183 | 0.7153 | 0.7599 | 0.7369 | 0.7490 | |
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| 0.5699 | 19.0 | 2565 | 0.7173 | 0.7122 | 0.7571 | 0.7340 | 0.7485 | |
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| 0.5699 | 20.0 | 2700 | 0.7179 | 0.7122 | 0.7571 | 0.7340 | 0.7485 | |
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### Framework versions |
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- Transformers 4.19.2 |
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- Pytorch 1.11.0+cu102 |
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- Datasets 2.2.2 |
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- Tokenizers 0.12.1 |
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