metadata
license: mit
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: deberta-v3-large-irony-lr8e-6-gas2-ls0.1
results: []
deberta-v3-large-irony-lr8e-6-gas2-ls0.1
This model is a fine-tuned version of microsoft/deberta-v3-large on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.7673
- Accuracy: 0.7675
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: 8e-06
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 50
- num_epochs: 10.0
- label_smoothing_factor: 0.1
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 0.6478 | 1.12 | 100 | 0.5890 | 0.7529 |
| 0.5013 | 2.25 | 200 | 0.5873 | 0.7707 |
| 0.388 | 3.37 | 300 | 0.6993 | 0.7602 |
| 0.3169 | 4.49 | 400 | 0.6773 | 0.7874 |
| 0.2693 | 5.61 | 500 | 0.7172 | 0.7707 |
| 0.2396 | 6.74 | 600 | 0.7397 | 0.7801 |
| 0.2284 | 7.86 | 700 | 0.8096 | 0.7550 |
| 0.2207 | 8.98 | 800 | 0.7827 | 0.7654 |
Framework versions
- Transformers 4.20.0.dev0
- Pytorch 1.9.0
- Datasets 2.2.2
- Tokenizers 0.11.6