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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-2-work-please
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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-2-work-please
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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: 0.7450
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- Accuracy: 0.8549
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- F1: 0.8516
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- Precision: 0.8714
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- Recall: 0.8327
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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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| 0.3685 | 1.0 | 7088 | 0.4334 | 0.8590 | 0.8463 | 0.9304 | 0.7762 |
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| 0.3721 | 2.0 | 14176 | 0.3822 | 0.8673 | 0.8575 | 0.9257 | 0.7987 |
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| 0.3393 | 3.0 | 21264 | 0.4634 | 0.8705 | 0.8619 | 0.9228 | 0.8086 |
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| 0.3017 | 4.0 | 28352 | 0.4806 | 0.8708 | 0.8630 | 0.9186 | 0.8137 |
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| 0.3072 | 5.0 | 35440 | 0.4509 | 0.87 | 0.8648 | 0.9009 | 0.8314 |
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| 0.2833 | 6.0 | 42528 | 0.5339 | 0.8627 | 0.8581 | 0.8879 | 0.8302 |
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| 0.2633 | 7.0 | 49616 | 0.5457 | 0.8637 | 0.8614 | 0.8759 | 0.8473 |
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| 0.2418 | 8.0 | 56704 | 0.6408 | 0.8589 | 0.8563 | 0.8722 | 0.8410 |
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| 0.1999 | 9.0 | 63792 | 0.7404 | 0.8530 | 0.8485 | 0.8752 | 0.8235 |
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| 0.1809 | 10.0 | 70880 | 0.7450 | 0.8549 | 0.8516 | 0.8714 | 0.8327 |
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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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