mistral_7b_0_3-summarize-gpt4o-128k
This model is a fine-tuned version of mistralai/Mistral-7B-v0.3 on the llama-duo/synth_summarize_dataset_dedup dataset. It achieves the following results on the evaluation set:
- Loss: 2.0012
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: 0.0002
- train_batch_size: 4
- eval_batch_size: 2
- seed: 42
- distributed_type: multi-GPU
- num_devices: 8
- gradient_accumulation_steps: 2
- total_train_batch_size: 64
- total_eval_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 10
Training results
Training Loss | Epoch | Step | Validation Loss |
---|---|---|---|
0.6982 | 0.9980 | 245 | 1.8248 |
0.6596 | 2.0 | 491 | 1.8338 |
0.6197 | 2.9980 | 736 | 1.8432 |
0.6011 | 4.0 | 982 | 1.8707 |
0.5805 | 4.9980 | 1227 | 1.9009 |
0.5585 | 6.0 | 1473 | 1.9298 |
0.5413 | 6.9980 | 1718 | 1.9540 |
0.5295 | 8.0 | 1964 | 1.9814 |
0.5154 | 8.9980 | 2209 | 1.9979 |
0.508 | 9.9796 | 2450 | 2.0012 |
Framework versions
- PEFT 0.12.0
- Transformers 4.44.0
- Pytorch 2.2.0+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1
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Model tree for llama-duo/mistral_7b_0_3-summarize-gpt4o-128k
Base model
mistralai/Mistral-7B-v0.3