metadata
library_name: transformers
license: other
base_model: DedalusHealthCare/tinybert-mlm-en
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
- precision
- recall
model-index:
- name: tinybert
results: []
tinybert
This model is a fine-tuned version of DedalusHealthCare/tinybert-mlm-en on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.5776
- Accuracy: 0.9816
- F1: 0.0
- Precision: 0.0
- Recall: 0.0
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: 2e-05
- train_batch_size: 32
- eval_batch_size: 16
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 20
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision | Recall |
|---|---|---|---|---|---|---|---|
| 0.7155 | 0.2857 | 1 | 0.7256 | 0.1969 | 0.0437 | 0.0224 | 1.0 |
| 0.7155 | 0.5714 | 2 | 0.7204 | 0.2283 | 0.0455 | 0.0233 | 1.0 |
| 0.7155 | 0.8571 | 3 | 0.7102 | 0.3333 | 0.0451 | 0.0232 | 0.8571 |
| 0.7155 | 1.1429 | 4 | 0.6954 | 0.4803 | 0.0388 | 0.0201 | 0.5714 |
| 0.7155 | 1.4286 | 5 | 0.6763 | 0.7008 | 0.0500 | 0.0265 | 0.4286 |
| 0.7155 | 1.7143 | 6 | 0.6533 | 0.8530 | 0.0345 | 0.0196 | 0.1429 |
| 0.7155 | 2.0 | 7 | 0.6268 | 0.9580 | 0.0 | 0.0 | 0.0 |
| 0.7155 | 2.2857 | 8 | 0.6016 | 0.9816 | 0.0 | 0.0 | 0.0 |
| 0.7155 | 2.5714 | 9 | 0.5776 | 0.9816 | 0.0 | 0.0 | 0.0 |
Framework versions
- Transformers 4.45.1
- Pytorch 2.6.0+cu124
- Datasets 2.16.0
- Tokenizers 0.20.3