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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_gl11 |
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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_gl11 |
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This model is a fine-tuned version of [vinayak361/token_fine_tunned_flipkart_2_gl7](https://huggingface.co/vinayak361/token_fine_tunned_flipkart_2_gl7) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.2288 |
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- Precision: 0.9084 |
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- Recall: 0.9229 |
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- F1: 0.9156 |
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- Accuracy: 0.9276 |
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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: 10 |
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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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| 0.362 | 1.0 | 1086 | 0.3079 | 0.8734 | 0.8941 | 0.8836 | 0.9012 | |
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| 0.3096 | 2.0 | 2172 | 0.2767 | 0.8858 | 0.9035 | 0.8946 | 0.9102 | |
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| 0.2806 | 3.0 | 3258 | 0.2591 | 0.8935 | 0.9111 | 0.9022 | 0.9167 | |
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| 0.2553 | 4.0 | 4344 | 0.2475 | 0.8989 | 0.9159 | 0.9073 | 0.9203 | |
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| 0.2372 | 5.0 | 5430 | 0.2400 | 0.9032 | 0.9184 | 0.9107 | 0.9237 | |
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| 0.2306 | 6.0 | 6516 | 0.2359 | 0.9060 | 0.9198 | 0.9128 | 0.9255 | |
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| 0.217 | 7.0 | 7602 | 0.2320 | 0.9063 | 0.9214 | 0.9138 | 0.9260 | |
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| 0.2048 | 8.0 | 8688 | 0.2302 | 0.9075 | 0.9226 | 0.9150 | 0.9268 | |
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| 0.2086 | 9.0 | 9774 | 0.2290 | 0.9086 | 0.9226 | 0.9155 | 0.9272 | |
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| 0.2072 | 10.0 | 10860 | 0.2288 | 0.9084 | 0.9229 | 0.9156 | 0.9276 | |
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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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