metadata
library_name: transformers
base_model: livinNector/m-minilm-l12-h384-dra-tam-mal-aw-setfit-finetune
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
model-index:
- name: m-minilm-l12-h384-dra-tam-mal-aw-setfit-double-finetune
results: []
m-minilm-l12-h384-dra-tam-mal-aw-setfit-double-finetune
This model is a fine-tuned version of livinNector/m-minilm-l12-h384-dra-tam-mal-aw-setfit-finetune on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.5252
- Accuracy: 0.7759
- F1: 0.7752
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: 0.0001
- train_batch_size: 128
- eval_batch_size: 128
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 6
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
|---|---|---|---|---|---|
| 0.6682 | 0.4444 | 20 | 0.6228 | 0.6659 | 0.6625 |
| 0.6171 | 0.8889 | 40 | 0.6035 | 0.6789 | 0.6756 |
| 0.5673 | 1.3333 | 60 | 0.5673 | 0.7188 | 0.7155 |
| 0.5481 | 1.7778 | 80 | 0.5864 | 0.6993 | 0.6937 |
| 0.5137 | 2.2222 | 100 | 0.5245 | 0.7465 | 0.7440 |
| 0.4527 | 2.6667 | 120 | 0.5279 | 0.7522 | 0.7506 |
| 0.4596 | 3.1111 | 140 | 0.5172 | 0.7579 | 0.7576 |
| 0.3943 | 3.5556 | 160 | 0.5366 | 0.7514 | 0.7514 |
| 0.3836 | 4.0 | 180 | 0.5387 | 0.7628 | 0.7627 |
| 0.3627 | 4.4444 | 200 | 0.5802 | 0.7490 | 0.7480 |
| 0.3302 | 4.8889 | 220 | 0.5616 | 0.7563 | 0.7563 |
| 0.2999 | 5.3333 | 240 | 0.5745 | 0.7620 | 0.7598 |
| 0.3061 | 5.7778 | 260 | 0.5651 | 0.7694 | 0.7689 |
Framework versions
- Transformers 4.47.1
- Pytorch 2.5.1+cu124
- Datasets 3.2.0
- Tokenizers 0.21.0