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lora_evo_ta_all_layers_2
This model is a fine-tuned version of togethercomputer/evo-1-8k-base on the None dataset. It achieves the following results on the evaluation set:
- Loss: 3.1660
Model description
lora_alpha = 32
lora_dropout = 0.05
lora_r = 16
epochs = 9 <---------------
learning rate = 3e-4
warmup_steps=0.5
gradient_accumulation_steps = 8
train_batch = 1
eval_batch = 1
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: 0.0003
- train_batch_size: 1
- eval_batch_size: 1
- seed: 42
- gradient_accumulation_steps: 8
- total_train_batch_size: 8
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: constant
- lr_scheduler_warmup_steps: 0.5
- num_epochs: 9
Training results
Training Loss | Epoch | Step | Validation Loss |
---|---|---|---|
3.0681 | 0.9925 | 33 | 2.9815 |
2.9165 | 1.9850 | 66 | 2.9530 |
2.8091 | 2.9774 | 99 | 2.9446 |
2.6361 | 4.0 | 133 | 2.9406 |
2.6312 | 4.9925 | 166 | 2.9409 |
2.57 | 5.9850 | 199 | 2.9978 |
2.5215 | 6.9774 | 232 | 3.0450 |
2.4107 | 8.0 | 266 | 3.0763 |
2.4272 | 8.9323 | 297 | 3.1660 |
Framework versions
- PEFT 0.11.1
- Transformers 4.41.1
- Pytorch 2.3.0+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1
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Model tree for lsmille/lora_evo_ta_all_layers_2
Base model
togethercomputer/evo-1-8k-base