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mlfoundations-dev_-_mistral_alpaca_sft_sample_2-gguf
RichardErkhov/mlfoundations-dev_-_mistral_alpaca_sft_sample_2-gguf
mlfoundations-dev_-_mistral_alpaca_sft_sample_2-gguf is a machine learning model from RichardErkhov. Use it for the machine learning task on the model card, and read the license before you ship it in a product.
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At a glance
- Access
- Public
- Created
- Apr 16, 2025
- Updated
- Apr 16, 2025
- SHA
- 415f1346
Model card
From the Hugging Face model README
Quantization made by Richard Erkhov.
mistral_alpaca_sft_sample_2 - GGUF
- Model creator: https://huggingface.co/mlfoundations-dev/
- Original model: https://huggingface.co/mlfoundations-dev/mistral_alpaca_sft_sample_2/
Original model description:
library_name: transformers license: apache-2.0 base_model: mistralai/Mistral-7B-v0.1 tags:
- llama-factory
- full
- generated_from_trainer model-index:
- name: mistral_alpaca_sft_sample_2 results: []
<!-- This model card has been generated automatically according to the information the Trainer had access to. You should probably proofread and complete it, then remove this comment. -->
mistral_alpaca_sft_sample_2
This model is a fine-tuned version of mistralai/Mistral-7B-v0.1 on the llamafactory/alpaca_en dataset. It achieves the following results on the evaluation set:
- Loss: 1.6961
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: 2e-05
- train_batch_size: 16
- eval_batch_size: 8
- seed: 42
- distributed_type: multi-GPU
- num_devices: 8
- gradient_accumulation_steps: 4
- total_train_batch_size: 512
- total_eval_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_ratio: 0.1
- training_steps: 3
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| No log | 0.1304 | 3 | 1.6961 |
Framework versions
- Transformers 4.45.2
- Pytorch 2.3.0
- Datasets 2.21.0
- Tokenizers 0.20.1
- Created
- Apr 16, 2025
- Updated
- Apr 16, 2025