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--- |
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license: mit |
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base_model: haryoaw/scenario-normal-finetune-clf-data-indolem_sentiment-model-xlm-roberta-base |
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tags: |
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- generated_from_trainer |
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datasets: |
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- indolem_sentiment |
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metrics: |
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- accuracy |
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- f1 |
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model-index: |
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- name: scenario-kd_weight_copy-data-indolem_sentiment-model-xlmr_base_trained |
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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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# scenario-kd_weight_copy-data-indolem_sentiment-model-xlmr_base_trained |
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This model is a fine-tuned version of [haryoaw/scenario-normal-finetune-clf-data-indolem_sentiment-model-xlm-roberta-base](https://huggingface.co/haryoaw/scenario-normal-finetune-clf-data-indolem_sentiment-model-xlm-roberta-base) on the indolem_sentiment dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 4.8332 |
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- Accuracy: 0.8471 |
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- F1: 0.7336 |
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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: 5e-05 |
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- train_batch_size: 32 |
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- eval_batch_size: 32 |
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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: 6969 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:| |
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| No log | 0.88 | 100 | 7.3908 | 0.7419 | 0.6601 | |
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| No log | 1.75 | 200 | 3.5626 | 0.8571 | 0.7816 | |
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| No log | 2.63 | 300 | 8.7677 | 0.7218 | 0.6706 | |
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| No log | 3.51 | 400 | 4.4989 | 0.8346 | 0.7402 | |
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| 3.8583 | 4.39 | 500 | 4.6632 | 0.8271 | 0.7273 | |
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| 3.8583 | 5.26 | 600 | 4.5488 | 0.8496 | 0.7619 | |
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| 3.8583 | 6.14 | 700 | 4.0955 | 0.8697 | 0.7759 | |
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| 3.8583 | 7.02 | 800 | 4.4503 | 0.8471 | 0.7404 | |
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| 3.8583 | 7.89 | 900 | 4.7169 | 0.8346 | 0.7556 | |
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| 1.2007 | 8.77 | 1000 | 3.8991 | 0.8697 | 0.7739 | |
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| 1.2007 | 9.65 | 1100 | 5.7272 | 0.8321 | 0.6794 | |
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| 1.2007 | 10.53 | 1200 | 4.7281 | 0.8596 | 0.7647 | |
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| 1.2007 | 11.4 | 1300 | 8.4804 | 0.8095 | 0.5682 | |
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| 1.2007 | 12.28 | 1400 | 4.2305 | 0.8546 | 0.7411 | |
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| 0.7006 | 13.16 | 1500 | 4.7921 | 0.8371 | 0.7137 | |
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| 0.7006 | 14.04 | 1600 | 4.6111 | 0.8471 | 0.7215 | |
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| 0.7006 | 14.91 | 1700 | 4.8332 | 0.8471 | 0.7336 | |
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### Framework versions |
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- Transformers 4.33.3 |
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- Pytorch 2.0.1 |
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- Datasets 2.14.5 |
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- Tokenizers 0.13.3 |
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