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--- |
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license: apache-2.0 |
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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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base_model: google/mt5-large |
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model-index: |
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- name: mt5_emotion_single |
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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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# mt5_emotion_single |
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This model is a fine-tuned version of [google/mt5-large](https://huggingface.co/google/mt5-large) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.6681 |
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- Accuracy: 0.805 |
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- Precision: 0.8255 |
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- Recall: 0.805 |
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- F1: 0.7872 |
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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: 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 | Precision | Recall | F1 | |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:| |
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| No log | 0.4 | 50 | 1.6075 | 0.205 | 0.2154 | 0.205 | 0.0906 | |
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| No log | 0.8 | 100 | 1.5035 | 0.385 | 0.2074 | 0.385 | 0.2506 | |
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| 1.5333 | 1.2 | 150 | 1.4960 | 0.44 | 0.4163 | 0.44 | 0.3830 | |
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| 1.5333 | 1.6 | 200 | 0.8993 | 0.73 | 0.7853 | 0.73 | 0.7005 | |
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| 0.7703 | 2.0 | 250 | 1.2461 | 0.63 | 0.6412 | 0.63 | 0.5691 | |
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| 0.7703 | 2.4 | 300 | 1.4746 | 0.58 | 0.5874 | 0.58 | 0.5419 | |
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| 0.7703 | 2.8 | 350 | 1.4532 | 0.605 | 0.6832 | 0.605 | 0.5636 | |
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### Framework versions |
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- Transformers 4.38.2 |
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- Pytorch 2.2.1+cu121 |
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- Datasets 2.18.0 |
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- Tokenizers 0.15.2 |
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