---
library_name: peft
license: apache-2.0
base_model: unsloth/mistral-7b-instruct-v0.3
tags:
- axolotl
- generated_from_trainer
model-index:
- name: 96935939-6069-4eca-96ff-cdae9e8cb7af
  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. -->

[<img src="https://raw.githubusercontent.com/axolotl-ai-cloud/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" width="200" height="32"/>](https://github.com/axolotl-ai-cloud/axolotl)
<details><summary>See axolotl config</summary>

axolotl version: `0.4.1`
```yaml
adapter: lora
base_model: unsloth/mistral-7b-instruct-v0.3
bf16: auto
chat_template: llama3
dataset_prepared_path: null
datasets:
- data_files:
  - 57978299522ad104_train_data.json
  ds_type: json
  format: custom
  path: /workspace/input_data/57978299522ad104_train_data.json
  type:
    field_instruction: prompt
    field_output: chosen
    format: '{instruction}'
    no_input_format: '{instruction}'
    system_format: '{system}'
    system_prompt: ''
debug: null
deepspeed: null
early_stopping_patience: null
eval_max_new_tokens: 128
eval_table_size: null
evals_per_epoch: 4
flash_attention: true
fp16: null
fsdp: null
fsdp_config: null
gradient_accumulation_steps: 4
gradient_checkpointing: true
gradient_clipping: 1.0
group_by_length: false
hub_model_id: brixeus/96935939-6069-4eca-96ff-cdae9e8cb7af
hub_repo: null
hub_strategy: checkpoint
hub_token: null
learning_rate: 5.0e-05
load_in_4bit: false
load_in_8bit: false
local_rank: 0
logging_steps: 3
lora_alpha: 32
lora_dropout: 0.05
lora_fan_in_fan_out: null
lora_model_dir: null
lora_r: 16
lora_target_linear: true
lr_scheduler: cosine
max_steps: 100
micro_batch_size: 8
mlflow_experiment_name: /tmp/57978299522ad104_train_data.json
model_type: AutoModelForCausalLM
num_epochs: 3
optimizer: adamw_bnb_8bit
output_dir: miner_id_24
pad_to_sequence_len: true
resume_from_checkpoint: null
s2_attention: null
sample_packing: false
saves_per_epoch: 4
sequence_len: 1024
strict: false
tf32: false
tokenizer_type: AutoTokenizer
train_on_inputs: false
trust_remote_code: true
val_set_size: 0.05
wandb_entity: techspear-hub
wandb_mode: online
wandb_name: 87ecf3ea-1b69-450f-b498-622c01e39891
wandb_project: Gradients-On-Three
wandb_run: your_name
wandb_runid: 87ecf3ea-1b69-450f-b498-622c01e39891
warmup_steps: 10
weight_decay: 0.01
xformers_attention: null

```

</details><br>

# 96935939-6069-4eca-96ff-cdae9e8cb7af

This model is a fine-tuned version of [unsloth/mistral-7b-instruct-v0.3](https://huggingface.co./unsloth/mistral-7b-instruct-v0.3) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 1.5946

## 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: 5e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 32
- optimizer: Use OptimizerNames.ADAMW_BNB with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: cosine
- lr_scheduler_warmup_steps: 10
- training_steps: 100

### Training results

| Training Loss | Epoch  | Step | Validation Loss |
|:-------------:|:------:|:----:|:---------------:|
| No log        | 0.0002 | 1    | 2.2963          |
| 8.4803        | 0.0018 | 9    | 1.8854          |
| 7.1409        | 0.0036 | 18   | 1.7100          |
| 6.7016        | 0.0054 | 27   | 1.6524          |
| 6.637         | 0.0072 | 36   | 1.6263          |
| 6.2794        | 0.0090 | 45   | 1.6119          |
| 6.2643        | 0.0108 | 54   | 1.6049          |
| 6.6138        | 0.0125 | 63   | 1.5997          |
| 6.0646        | 0.0143 | 72   | 1.5968          |
| 6.0643        | 0.0161 | 81   | 1.5953          |
| 6.6755        | 0.0179 | 90   | 1.5948          |
| 6.0766        | 0.0197 | 99   | 1.5946          |


### Framework versions

- PEFT 0.13.2
- Transformers 4.46.0
- Pytorch 2.5.0+cu124
- Datasets 3.0.1
- Tokenizers 0.20.1