mt5_emotion_single
This model is a fine-tuned version of google/mt5-large on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.6681
- Accuracy: 0.805
- Precision: 0.8255
- Recall: 0.805
- F1: 0.7872
Model description
More information needed
Intended uses & limitations
More information needed
Training and evaluation data
More information needed
Training procedure
Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 5e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10
Training results
Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 |
---|---|---|---|---|---|---|---|
No log | 0.4 | 50 | 1.6075 | 0.205 | 0.2154 | 0.205 | 0.0906 |
No log | 0.8 | 100 | 1.5035 | 0.385 | 0.2074 | 0.385 | 0.2506 |
1.5333 | 1.2 | 150 | 1.4960 | 0.44 | 0.4163 | 0.44 | 0.3830 |
1.5333 | 1.6 | 200 | 0.8993 | 0.73 | 0.7853 | 0.73 | 0.7005 |
0.7703 | 2.0 | 250 | 1.2461 | 0.63 | 0.6412 | 0.63 | 0.5691 |
0.7703 | 2.4 | 300 | 1.4746 | 0.58 | 0.5874 | 0.58 | 0.5419 |
0.7703 | 2.8 | 350 | 1.4532 | 0.605 | 0.6832 | 0.605 | 0.5636 |
Framework versions
- Transformers 4.38.2
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2
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Model tree for Holmeister/mt5_emotion_single
Base model
google/mt5-large