token-classification-llmlingua2-phobert-bctn-323_sample-5_epoch_16k_fpt_v1
This model is a fine-tuned version of vinai/phobert-base-v2 on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.6698
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: 1
- eval_batch_size: 1
- seed: 42
- gradient_accumulation_steps: 16
- total_train_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| No log | 0.99 | 16 | 0.6736 |
| No log | 1.98 | 32 | 0.6717 |
| No log | 2.98 | 48 | 0.6711 |
| No log | 3.97 | 64 | 0.6702 |
| No log | 4.96 | 80 | 0.6698 |
Framework versions
- Transformers 4.39.0.dev0
- Pytorch 2.2.1+cu118
- Datasets 2.18.0
- Tokenizers 0.15.2
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Model tree for qminh369/token-classification-llmlingua2-phobert-bctn-323_sample-5_epoch_16k_fpt_v1
Base model
vinai/phobert-base-v2