metadata
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- accuracy
- precision
- recall
- f1
base_model: google/mt5-large
model-index:
- name: mt5_emotion_multi
results: []
mt5_emotion_multi
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: 0.3993
- Accuracy: 0.901
- Precision: 0.9037
- Recall: 0.901
- F1: 0.9008
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 | 1.6030 | 0.405 | 0.2816 | 0.405 | 0.3089 |
| No log | 0.8 | 100 | 1.3838 | 0.5 | 0.5244 | 0.5 | 0.3826 |
| 1.5266 | 1.2 | 150 | 1.1754 | 0.535 | 0.6592 | 0.535 | 0.4998 |
| 1.5266 | 1.6 | 200 | 1.0208 | 0.645 | 0.7211 | 0.645 | 0.6155 |
| 0.7436 | 2.0 | 250 | 0.7959 | 0.735 | 0.8247 | 0.735 | 0.7121 |
| 0.7436 | 2.4 | 300 | 0.6869 | 0.79 | 0.8289 | 0.79 | 0.7871 |
| 0.7436 | 2.8 | 350 | 0.6828 | 0.805 | 0.8335 | 0.805 | 0.7983 |
| 0.2185 | 3.2 | 400 | 1.0537 | 0.75 | 0.8211 | 0.75 | 0.7343 |
| 0.2185 | 3.6 | 450 | 0.5383 | 0.85 | 0.8587 | 0.85 | 0.8474 |
| 0.1285 | 4.0 | 500 | 0.9033 | 0.795 | 0.8512 | 0.795 | 0.7851 |
| 0.1285 | 4.4 | 550 | 1.1142 | 0.755 | 0.8272 | 0.755 | 0.7371 |
| 0.1285 | 4.8 | 600 | 1.0917 | 0.77 | 0.8302 | 0.77 | 0.7640 |
Framework versions
- Transformers 4.38.2
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2