distilbert-base-uncased-finetuned-sst-2-english_08112024T121529
This model is a fine-tuned version of distilbert/distilbert-base-uncased-finetuned-sst-2-english on the None dataset. It achieves the following results on the evaluation set:
- Loss: 1.0521
- F1: 0.5770
- Learning Rate: 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: 0.001
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_steps: 600
- num_epochs: 20
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | F1 | Rate |
|---|---|---|---|---|---|
| No log | 0.9942 | 86 | 1.0521 | 0.5770 | 0.0001 |
| No log | 2.0 | 173 | 1.0938 | 0.6023 | 0.0003 |
| No log | 2.9942 | 259 | 1.1901 | 0.6153 | 0.0004 |
| No log | 4.0 | 346 | 1.1094 | 0.6056 | 0.0006 |
| No log | 4.9942 | 432 | 1.2608 | 0.4934 | 0.0007 |
| 1.1523 | 6.0 | 519 | 1.2942 | 0.5451 | 0.0009 |
| 1.1523 | 6.9942 | 605 | 1.2737 | 0.5362 | 0.001 |
| 1.1523 | 8.0 | 692 | 1.2844 | 0.4450 | 0.0010 |
| 1.1523 | 8.9942 | 778 | 1.6545 | 0.2937 | 0.0009 |
| 1.1523 | 10.0 | 865 | 1.4726 | 0.3773 | 0.0009 |
| 1.1523 | 10.9942 | 951 | 1.5591 | 0.3796 | 0.0008 |
| 1.367 | 12.0 | 1038 | 1.4358 | 0.4459 | 0.0007 |
| 1.367 | 12.9942 | 1124 | 1.4144 | 0.4272 | 0.0006 |
| 1.367 | 14.0 | 1211 | 1.3512 | 0.4938 | 0.0004 |
| 1.367 | 14.9942 | 1297 | 1.2704 | 0.5067 | 0.0003 |
| 1.367 | 16.0 | 1384 | 1.2057 | 0.5329 | 0.0002 |
| 1.367 | 16.9942 | 1470 | 1.1236 | 0.5658 | 0.0001 |
| 1.206 | 18.0 | 1557 | 1.1138 | 0.5826 | 0.0001 |
| 1.206 | 18.9942 | 1643 | 1.0703 | 0.6122 | 0.0000 |
| 1.206 | 19.8844 | 1720 | 1.0771 | 0.6069 | 0.0 |
Framework versions
- Transformers 4.44.2
- Pytorch 2.5.1+cu124
- Datasets 3.1.0
- Tokenizers 0.19.1
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