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token_fine_tunned_flipkart_2_gl6

Token Classification
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distilbert
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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_gl6
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+ results: []
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+ ---
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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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+
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+ # token_fine_tunned_flipkart_2_gl6
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+
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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: 0.7363
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+ - Precision: 0.7243
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+ - Recall: 0.7752
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+ - F1: 0.7489
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+ - Accuracy: 0.7558
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+
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+ ## Model description
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+
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+ More information needed
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+
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+ ## Intended uses & limitations
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+
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+ More information needed
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+
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+ ## Training and evaluation data
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+
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+ More information needed
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+
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+ ## Training procedure
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+
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+ ### Training hyperparameters
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+
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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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+
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+ ### Training results
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+
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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 | 120 | 1.0057 | 0.6623 | 0.7212 | 0.6905 | 0.6995 |
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+ | No log | 2.0 | 240 | 0.8581 | 0.6660 | 0.7290 | 0.6961 | 0.7080 |
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+ | No log | 3.0 | 360 | 0.8085 | 0.6882 | 0.7518 | 0.7186 | 0.7302 |
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+ | No log | 4.0 | 480 | 0.7890 | 0.6970 | 0.7575 | 0.7260 | 0.7332 |
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+ | 0.92 | 5.0 | 600 | 0.7716 | 0.7036 | 0.7596 | 0.7305 | 0.7372 |
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+ | 0.92 | 6.0 | 720 | 0.7573 | 0.7028 | 0.7603 | 0.7304 | 0.7397 |
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+ | 0.92 | 7.0 | 840 | 0.7510 | 0.7135 | 0.7653 | 0.7385 | 0.7462 |
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+ | 0.92 | 8.0 | 960 | 0.7509 | 0.7192 | 0.7688 | 0.7432 | 0.7472 |
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+ | 0.7004 | 9.0 | 1080 | 0.7409 | 0.7181 | 0.7717 | 0.7439 | 0.7472 |
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+ | 0.7004 | 10.0 | 1200 | 0.7428 | 0.7155 | 0.7710 | 0.7422 | 0.7492 |
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+ | 0.7004 | 11.0 | 1320 | 0.7414 | 0.7223 | 0.7752 | 0.7479 | 0.7523 |
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+ | 0.7004 | 12.0 | 1440 | 0.7426 | 0.7207 | 0.7710 | 0.7450 | 0.7492 |
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+ | 0.6265 | 13.0 | 1560 | 0.7368 | 0.7255 | 0.7745 | 0.7492 | 0.7553 |
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+ | 0.6265 | 14.0 | 1680 | 0.7388 | 0.7239 | 0.7738 | 0.7480 | 0.7538 |
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+ | 0.6265 | 15.0 | 1800 | 0.7338 | 0.7239 | 0.7738 | 0.7480 | 0.7538 |
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+ | 0.6265 | 16.0 | 1920 | 0.7368 | 0.7243 | 0.7752 | 0.7489 | 0.7548 |
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+ | 0.5879 | 17.0 | 2040 | 0.7371 | 0.7270 | 0.7767 | 0.7510 | 0.7568 |
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+ | 0.5879 | 18.0 | 2160 | 0.7371 | 0.7243 | 0.7752 | 0.7489 | 0.7558 |
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+ | 0.5879 | 19.0 | 2280 | 0.7356 | 0.7247 | 0.7752 | 0.7491 | 0.7553 |
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+ | 0.5879 | 20.0 | 2400 | 0.7363 | 0.7243 | 0.7752 | 0.7489 | 0.7558 |
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+
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+
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+ ### Framework versions
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+
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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