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update model card README.md
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README.md
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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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- accuracy
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- f1
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- precision
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- recall
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model-index:
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- name: sentiment-10Epochs
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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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# sentiment-10Epochs
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This model is a fine-tuned version of [xlm-roberta-base](https://huggingface.co/xlm-roberta-base) on an unknown dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.7030
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- Accuracy: 0.8603
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- F1: 0.8585
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- Precision: 0.8699
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- Recall: 0.8473
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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-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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| 0.3645 | 1.0 | 7088 | 0.4315 | 0.8603 | 0.8466 | 0.9386 | 0.7711 |
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| 0.374 | 2.0 | 14176 | 0.4015 | 0.8713 | 0.8648 | 0.9105 | 0.8235 |
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| 0.3363 | 3.0 | 21264 | 0.4772 | 0.8705 | 0.8615 | 0.9256 | 0.8057 |
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| 0.3131 | 4.0 | 28352 | 0.4579 | 0.8702 | 0.8650 | 0.9007 | 0.8321 |
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| 0.3097 | 5.0 | 35440 | 0.4160 | 0.8721 | 0.8663 | 0.9069 | 0.8292 |
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| 0.2921 | 6.0 | 42528 | 0.4638 | 0.8673 | 0.8630 | 0.8917 | 0.8362 |
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| 0.2725 | 7.0 | 49616 | 0.5183 | 0.8654 | 0.8602 | 0.8947 | 0.8283 |
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| 0.2481 | 8.0 | 56704 | 0.5846 | 0.8649 | 0.8624 | 0.8787 | 0.8467 |
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| 0.192 | 9.0 | 63792 | 0.6481 | 0.8610 | 0.8596 | 0.8680 | 0.8514 |
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| 0.1945 | 10.0 | 70880 | 0.7030 | 0.8603 | 0.8585 | 0.8699 | 0.8473 |
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### Framework versions
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- Transformers 4.18.0
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- Pytorch 1.10.0
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- Datasets 2.0.0
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- Tokenizers 0.11.6
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