financial_statements
This model is a fine-tuned version of togethercomputer/Llama-2-7B-32K-Instruct on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.0511
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: 4
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_ratio: 0.05
- num_epochs: 2
- mixed_precision_training: Native AMP
Training results
Training Loss | Epoch | Step | Validation Loss |
---|---|---|---|
0.0532 | 0.6667 | 100 | 0.1025 |
0.1298 | 1.3333 | 200 | 0.0780 |
0.0556 | 2.0 | 300 | 0.0511 |
Framework versions
- PEFT 0.12.0
- Transformers 4.42.4
- Pytorch 2.4.0+cu121
- Datasets 2.21.0
- Tokenizers 0.19.1
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Model tree for GoldenSnitch12/financial_statements
Base model
togethercomputer/Llama-2-7B-32K-Instruct