flan-t5-base-skill-extraction-lora-ver1
This model is a fine-tuned version of google/flan-t5-base on the None dataset. It achieves the following results on the evaluation set:
- Loss: 1.1084
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: 0.0001
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 16
- optimizer: Use OptimizerNames.ADAMW_8BIT with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: cosine
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 10
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 1.9885 | 0.5051 | 300 | 1.5889 |
| 1.5829 | 1.0101 | 600 | 1.3672 |
| 1.4693 | 1.5152 | 900 | 1.2715 |
| 1.4251 | 2.0202 | 1200 | 1.2314 |
| 1.3995 | 2.5253 | 1500 | 1.2070 |
| 1.3413 | 3.0303 | 1800 | 1.1826 |
| 1.3164 | 3.5354 | 2100 | 1.1602 |
| 1.2953 | 4.0404 | 2400 | 1.1533 |
| 1.3004 | 4.5455 | 2700 | 1.1426 |
| 1.2823 | 5.0505 | 3000 | 1.1328 |
| 1.263 | 5.5556 | 3300 | 1.1328 |
| 1.2396 | 6.0606 | 3600 | 1.1230 |
| 1.2127 | 6.5657 | 3900 | 1.1201 |
| 1.1944 | 7.0707 | 4200 | 1.1162 |
| 1.2369 | 7.5758 | 4500 | 1.1104 |
| 1.2336 | 8.0808 | 4800 | 1.1094 |
| 1.1903 | 8.5859 | 5100 | 1.1094 |
| 1.2043 | 9.0909 | 5400 | 1.1084 |
| 1.2145 | 9.5960 | 5700 | 1.1084 |
Framework versions
- PEFT 0.10.0
- Transformers 4.49.0
- Pytorch 2.4.1+cu118
- Datasets 4.1.1
- Tokenizers 0.21.0
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Base model
google/flan-t5-base