vicuna_1b_stage1
This model is a fine-tuned version of Jiayi-Pan/Tiny-Vicuna-1B on the Aeala/ShareGPT_Vicuna_unfiltered dataset. It achieves the following results on the evaluation set:
- Loss: 2.9673
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: 0.0005
- train_batch_size: 2
- eval_batch_size: 2
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 8
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_steps: 40
- num_epochs: 1
Training results
Training Loss | Epoch | Step | Validation Loss |
---|---|---|---|
3.3461 | 0.0170 | 40 | 3.5421 |
3.2004 | 0.0340 | 80 | 3.1581 |
3.0095 | 0.0510 | 120 | 3.0506 |
2.714 | 0.0681 | 160 | 3.0168 |
2.9508 | 0.0851 | 200 | 2.9764 |
2.9774 | 0.1021 | 240 | 2.9598 |
2.8688 | 0.1191 | 280 | 2.9551 |
2.8195 | 0.1361 | 320 | 2.9420 |
2.8471 | 0.1531 | 360 | 2.9328 |
2.9252 | 0.1701 | 400 | 2.9673 |
Framework versions
- Transformers 4.43.0
- Pytorch 2.3.1
- Datasets 2.15.0
- Tokenizers 0.19.1
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Model tree for Momorami/medusa-vicuna_1b_stage1
Base model
Jiayi-Pan/Tiny-Vicuna-1B