---
library_name: peft
license: gemma
base_model: unsloth/gemma-2-2b-it
tags:
- axolotl
- generated_from_trainer
model-index:
- name: f11e9dd7-c7de-4f97-9479-ba5c0483a0e4
  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/gemma-2-2b-it
bf16: true
chat_template: llama3
dataset_prepared_path: null
datasets:
- data_files:
  - 5dc5562c268ed6f8_train_data.json
  ds_type: json
  format: custom
  path: /workspace/input_data/5dc5562c268ed6f8_train_data.json
  type:
    field_input: original_version
    field_instruction: title
    field_output: french_version
    format: '{instruction} {input}'
    no_input_format: '{instruction}'
    system_format: '{system}'
    system_prompt: ''
debug: null
device_map:
  ? ''
  : 0,1,2,3,4,5,6,7
early_stopping_patience: 2
eval_max_new_tokens: 128
eval_steps: 400
eval_table_size: null
flash_attention: false
gradient_accumulation_steps: 4
gradient_checkpointing: true
group_by_length: false
hub_model_id: Alphatao/f11e9dd7-c7de-4f97-9479-ba5c0483a0e4
hub_repo: null
hub_strategy: null
hub_token: null
learning_rate: 0.0002
load_best_model_at_end: true
load_in_4bit: false
load_in_8bit: false
local_rank: null
logging_steps: 1
lora_alpha: 32
lora_dropout: 0.05
lora_fan_in_fan_out: null
lora_model_dir: null
lora_r: 16
lora_target_linear: true
lora_target_modules:
- q_proj
- k_proj
- v_proj
- o_proj
lr_scheduler: cosine
max_grad_norm: 1.0
max_steps: 7258
micro_batch_size: 2
mlflow_experiment_name: /tmp/5dc5562c268ed6f8_train_data.json
model_type: AutoModelForCausalLM
num_epochs: 2
optimizer: adamw_bnb_8bit
output_dir: miner_id_24
pad_to_sequence_len: true
resume_from_checkpoint: null
s2_attention: null
sample_packing: false
save_steps: 400
sequence_len: 1024
strict: false
tf32: true
tokenizer_type: AutoTokenizer
train_on_inputs: false
trust_remote_code: true
val_set_size: 0.05
wandb_entity: null
wandb_mode: online
wandb_name: 4ed3c119-858f-4aa1-a7e8-0ec4deb92bdb
wandb_project: Gradients-On-Demand
wandb_run: your_name
wandb_runid: 4ed3c119-858f-4aa1-a7e8-0ec4deb92bdb
warmup_steps: 10
weight_decay: 0.0
xformers_attention: null

```

</details><br>

# f11e9dd7-c7de-4f97-9479-ba5c0483a0e4

This model is a fine-tuned version of [unsloth/gemma-2-2b-it](https://huggingface.co/unsloth/gemma-2-2b-it) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.9316

## 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: 0.0002
- train_batch_size: 2
- eval_batch_size: 2
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 8
- 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: 7258

### Training results

| Training Loss | Epoch  | Step | Validation Loss |
|:-------------:|:------:|:----:|:---------------:|
| 0.9599        | 0.0001 | 1    | 1.3887          |
| 1.1727        | 0.0342 | 400  | 1.0594          |
| 0.4701        | 0.0684 | 800  | 1.0372          |
| 0.909         | 0.1026 | 1200 | 1.0207          |
| 1.2693        | 0.1368 | 1600 | 1.0106          |
| 1.0021        | 0.1710 | 2000 | 1.0011          |
| 0.6727        | 0.2052 | 2400 | 0.9943          |
| 0.9811        | 0.2394 | 2800 | 0.9838          |
| 1.3031        | 0.2736 | 3200 | 0.9744          |
| 0.5804        | 0.3078 | 3600 | 0.9673          |
| 0.6857        | 0.3420 | 4000 | 0.9602          |
| 0.8827        | 0.3762 | 4400 | 0.9520          |
| 1.0814        | 0.4104 | 4800 | 0.9460          |
| 0.4212        | 0.4446 | 5200 | 0.9410          |
| 1.0149        | 0.4788 | 5600 | 0.9374          |
| 0.6131        | 0.5130 | 6000 | 0.9345          |
| 0.6607        | 0.5472 | 6400 | 0.9326          |
| 0.8703        | 0.5814 | 6800 | 0.9318          |
| 1.2847        | 0.6156 | 7200 | 0.9316          |


### Framework versions

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