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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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- precision |
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- recall |
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- f1 |
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model-index: |
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- name: xlm-roberta-base-finetuned-code-mixed-DS |
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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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# xlm-roberta-base-finetuned-code-mixed-DS |
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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: 0.8266 |
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- Accuracy: 0.6318 |
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- Precision: 0.5781 |
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- Recall: 0.5978 |
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- F1: 0.5677 |
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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: 4.932923543227153e-05 |
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- train_batch_size: 16 |
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- eval_batch_size: 32 |
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- seed: 43 |
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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: 4 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 | |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:| |
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| 1.0602 | 1.0 | 248 | 1.0280 | 0.5211 | 0.4095 | 0.4557 | 0.3912 | |
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| 0.9741 | 1.99 | 496 | 0.9318 | 0.5533 | 0.4758 | 0.5002 | 0.4415 | |
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| 0.8585 | 2.99 | 744 | 0.8585 | 0.6076 | 0.5539 | 0.5731 | 0.5353 | |
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| 0.7293 | 3.98 | 992 | 0.8266 | 0.6318 | 0.5781 | 0.5978 | 0.5677 | |
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### Framework versions |
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- Transformers 4.20.1 |
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- Pytorch 1.10.1+cu111 |
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- Datasets 2.3.2 |
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- Tokenizers 0.12.1 |
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