Downloads · 30 days
1
4% of all-time downloads
tsavage68_-_Hyponatremia_M2_150steps_1e7rate_SFT-4bits
RichardErkhov/tsavage68_-_Hyponatremia_M2_150steps_1e7rate_SFT-4bits
tsavage68_-_Hyponatremia_M2_150steps_1e7rate_SFT-4bits 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.
All-time downloads
25
Public
Parameters
7.4B
4.5 GB on disk
Likes
0
Public
Repo makeup
Click a slice to open those files.
.safetensors4.5 GB · 100%
Parameter types
How the weights are stored.
U87B · 95%
Model card
From the Hugging Face model README
Quantization made by Richard Erkhov.
Hyponatremia_M2_150steps_1e7rate_SFT - bnb 4bits
- Model creator: https://huggingface.co/tsavage68/
- Original model: https://huggingface.co/tsavage68/Hyponatremia_M2_150steps_1e7rate_SFT/
Original model description:
license: apache-2.0 base_model: mistralai/Mistral-7B-Instruct-v0.2 tags:
- trl
- sft
- generated_from_trainer model-index:
- name: Hyponatremia_M2_150steps_1e7rate_SFT 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. -->
Hyponatremia_M2_150steps_1e7rate_SFT
This model is a fine-tuned version of mistralai/Mistral-7B-Instruct-v0.2 on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.3288
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-07
- train_batch_size: 2
- eval_batch_size: 1
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 4
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_steps: 100
- training_steps: 150
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 2.039 | 0.2667 | 50 | 1.9360 |
| 0.7076 | 0.5333 | 100 | 0.5643 |
| 0.329 | 0.8 | 150 | 0.3288 |
Framework versions
- Transformers 4.42.3
- Pytorch 2.0.0+cu117
- Datasets 2.20.0
- Tokenizers 0.19.1
- Type
- mistral
- Created
- Mar 19, 2025
- Updated
- Mar 19, 2025