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roberta-finetuned-WebClassification-v2-smalllinguaMultiv2

Text Classification
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PyTorch
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roberta
Generated from Trainer
text-embeddings-inference
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María Navas Loro commited on
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update model card README.md

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@@ -19,11 +19,11 @@ should probably proofread and complete it, then remove this comment. -->
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  This model is a fine-tuned version of [xlm-roberta-base](https://huggingface.co/xlm-roberta-base) on the None dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 1.0950
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- - Accuracy: 0.7742
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- - F1: 0.7742
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- - Precision: 0.7742
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- - Recall: 0.7742
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  ## Model description
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  The following hyperparameters were used during training:
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  - learning_rate: 2e-05
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- - train_batch_size: 8
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- - eval_batch_size: 8
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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 | Accuracy | F1 | Precision | Recall |
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  |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|
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- | No log | 1.0 | 48 | 2.8245 | 0.2796 | 0.2796 | 0.2796 | 0.2796 |
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- | No log | 2.0 | 96 | 2.2338 | 0.4301 | 0.4301 | 0.4301 | 0.4301 |
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- | No log | 3.0 | 144 | 1.9060 | 0.5269 | 0.5269 | 0.5269 | 0.5269 |
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- | No log | 4.0 | 192 | 1.5349 | 0.6022 | 0.6022 | 0.6022 | 0.6022 |
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- | No log | 5.0 | 240 | 1.4208 | 0.6882 | 0.6882 | 0.6882 | 0.6882 |
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- | No log | 6.0 | 288 | 1.3330 | 0.7204 | 0.7204 | 0.7204 | 0.7204 |
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- | No log | 7.0 | 336 | 1.2037 | 0.7097 | 0.7097 | 0.7097 | 0.7097 |
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- | No log | 8.0 | 384 | 1.1414 | 0.7419 | 0.7419 | 0.7419 | 0.7419 |
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- | No log | 9.0 | 432 | 1.0950 | 0.7742 | 0.7742 | 0.7742 | 0.7742 |
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- | No log | 10.0 | 480 | 1.0883 | 0.7634 | 0.7634 | 0.7634 | 0.7634 |
 
 
 
 
 
 
 
 
 
 
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  ### Framework versions
 
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  This model is a fine-tuned version of [xlm-roberta-base](https://huggingface.co/xlm-roberta-base) on the None dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.8644
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+ - Accuracy: 0.8387
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+ - F1: 0.8387
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+ - Precision: 0.8387
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+ - Recall: 0.8387
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  ## Model description
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  The following hyperparameters were used during training:
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  - learning_rate: 2e-05
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+ - train_batch_size: 4
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+ - eval_batch_size: 4
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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 | Accuracy | F1 | Precision | Recall |
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  |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|
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+ | No log | 1.0 | 95 | 2.3654 | 0.4409 | 0.4409 | 0.4409 | 0.4409 |
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+ | No log | 2.0 | 190 | 1.8455 | 0.5269 | 0.5269 | 0.5269 | 0.5269 |
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+ | No log | 3.0 | 285 | 1.4468 | 0.6344 | 0.6344 | 0.6344 | 0.6344 |
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+ | No log | 4.0 | 380 | 1.1099 | 0.7419 | 0.7419 | 0.7419 | 0.7419 |
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+ | No log | 5.0 | 475 | 1.0515 | 0.7634 | 0.7634 | 0.7634 | 0.7634 |
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+ | 1.6355 | 6.0 | 570 | 0.9938 | 0.7312 | 0.7312 | 0.7312 | 0.7312 |
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+ | 1.6355 | 7.0 | 665 | 0.8275 | 0.7957 | 0.7957 | 0.7957 | 0.7957 |
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+ | 1.6355 | 8.0 | 760 | 0.8344 | 0.7957 | 0.7957 | 0.7957 | 0.7957 |
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+ | 1.6355 | 9.0 | 855 | 0.8516 | 0.8065 | 0.8065 | 0.8065 | 0.8065 |
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+ | 1.6355 | 10.0 | 950 | 0.8723 | 0.7957 | 0.7957 | 0.7957 | 0.7957 |
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+ | 0.2827 | 11.0 | 1045 | 0.8644 | 0.8387 | 0.8387 | 0.8387 | 0.8387 |
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+ | 0.2827 | 12.0 | 1140 | 0.9343 | 0.8065 | 0.8065 | 0.8065 | 0.8065 |
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+ | 0.2827 | 13.0 | 1235 | 1.0181 | 0.7957 | 0.7957 | 0.7957 | 0.7957 |
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+ | 0.2827 | 14.0 | 1330 | 1.0068 | 0.7957 | 0.7957 | 0.7957 | 0.7957 |
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+ | 0.2827 | 15.0 | 1425 | 1.0085 | 0.8065 | 0.8065 | 0.8065 | 0.8065 |
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+ | 0.0485 | 16.0 | 1520 | 1.0257 | 0.8280 | 0.8280 | 0.8280 | 0.8280 |
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+ | 0.0485 | 17.0 | 1615 | 1.0305 | 0.8172 | 0.8172 | 0.8172 | 0.8172 |
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+ | 0.0485 | 18.0 | 1710 | 1.0648 | 0.7957 | 0.7957 | 0.7957 | 0.7957 |
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+ | 0.0485 | 19.0 | 1805 | 1.0677 | 0.7957 | 0.7957 | 0.7957 | 0.7957 |
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+ | 0.0485 | 20.0 | 1900 | 1.0687 | 0.7957 | 0.7957 | 0.7957 | 0.7957 |
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  ### Framework versions