Llama-3.1-8B-Instruct-sum_train
This model is a fine-tuned version of NousResearch/Meta-Llama-3.1-8B-Instruct on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 1.3087
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: 1e-05
- train_batch_size: 1
- eval_batch_size: 1
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 2
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 1
Training results
Training Loss | Epoch | Step | Validation Loss |
---|---|---|---|
1.3229 | 0.3375 | 300 | 1.3282 |
1.2319 | 0.6749 | 600 | 1.3087 |
Framework versions
- PEFT 0.11.2.dev0
- Transformers 4.43.2
- Pytorch 2.3.0+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1
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Model tree for slavamarcin/Llama-3.1-8B-Instruct-sum_train
Base model
NousResearch/Meta-Llama-3.1-8B-Instruct