metadata
license: mit
base_model: VuongQuoc/checkpoints_26_9_microsoft_deberta_21_9
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: checkpoints_27_9_microsoft_deberta_21_9
results: []
checkpoints_27_9_microsoft_deberta_21_9
This model is a fine-tuned version of VuongQuoc/checkpoints_26_9_microsoft_deberta_21_9 on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.6632
- Map@3: 0.8608
- Accuracy: 0.775
- MAX_INPUT = 256
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: 1e-05
- train_batch_size: 2
- eval_batch_size: 4
- seed: 42
- gradient_accumulation_steps: 16
- total_train_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_ratio: 0.2
- num_epochs: 1
Training results
| Training Loss | Epoch | Step | Validation Loss | Map@3 | Accuracy |
|---|---|---|---|---|---|
| 0.6308 | 0.05 | 100 | 0.6775 | 0.8842 | 0.815 |
| 0.3472 | 0.11 | 200 | 0.7255 | 0.8767 | 0.805 |
| 0.2267 | 0.16 | 300 | 0.7786 | 0.8608 | 0.785 |
| 0.143 | 0.21 | 400 | 0.8580 | 0.8333 | 0.735 |
| 0.0723 | 0.27 | 500 | 0.9517 | 0.8358 | 0.735 |
| 0.3952 | 0.32 | 600 | 0.6632 | 0.8608 | 0.775 |
Framework versions
- Transformers 4.32.1
- Pytorch 2.0.0
- Datasets 2.9.0
- Tokenizers 0.13.3