metadata
language:
- multilingual
base_model: /kaggle/input/mistral-7b/Mistral-7B-v0.1
tags:
- generated_from_trainer
datasets:
- STEM
model-index:
- name: mistral-7b-llm-science-exam
results: []
mistral-7b-llm-science-exam
This model is a fine-tuned version of /kaggle/input/mistral-7b/Mistral-7B-v0.1 on the llm-science-exam dataset. It achieves the following results on the evaluation set:
- Loss: 0.3951
- Map@3: 0.8976
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: 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: 50
- num_epochs: 1
Training results
| Training Loss | Epoch | Step | Validation Loss | Map@3 |
|---|---|---|---|---|
| 3.3769 | 0.11 | 50 | 1.8621 | 0.9238 |
| 1.5772 | 0.23 | 100 | 0.5619 | 0.9119 |
| 0.9202 | 0.34 | 150 | 0.3942 | 0.9095 |
| 0.9485 | 0.45 | 200 | 0.4117 | 0.8976 |
| 0.9698 | 0.56 | 250 | 0.4145 | 0.9048 |
| 0.8731 | 0.68 | 300 | 0.4054 | 0.9048 |
| 0.8929 | 0.79 | 350 | 0.3967 | 0.8976 |
| 0.9737 | 0.9 | 400 | 0.3951 | 0.8976 |
Framework versions
- Transformers 4.34.0.dev0
- Pytorch 2.0.0
- Datasets 2.14.4
- Tokenizers 0.14.0