---
library_name: peft
base_model: rayonlabs/merged-merged-af6dd40b-32e1-43b1-adfd-8ce14d65d738-PubMedQA-138437bf-44bd-4b03-8801-d05451a9ff28
tags:
- axolotl
- generated_from_trainer
model-index:
- name: 8fd47b84-dd93-4a76-93c5-e9e7ae76c80f
  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: rayonlabs/merged-merged-af6dd40b-32e1-43b1-adfd-8ce14d65d738-PubMedQA-138437bf-44bd-4b03-8801-d05451a9ff28
bf16: auto
chat_template: llama3
dataset_prepared_path: null
datasets:
- data_files:
  - d37d23a80d00d27e_train_data.json
  ds_type: json
  format: custom
  path: /workspace/input_data/d37d23a80d00d27e_train_data.json
  type:
    field_input: context
    field_instruction: question
    field_output: final_decision
    format: '{instruction} {input}'
    no_input_format: '{instruction}'
    system_format: '{system}'
    system_prompt: ''
debug: null
deepspeed: null
device: cuda
early_stopping_patience: null
eval_max_new_tokens: 128
eval_table_size: null
evals_per_epoch: 4
flash_attention: false
fp16: null
gradient_accumulation_steps: 4
gradient_checkpointing: false
group_by_length: false
hub_model_id: dimasik2987/8fd47b84-dd93-4a76-93c5-e9e7ae76c80f
hub_repo: null
hub_strategy: checkpoint
hub_token: null
learning_rate: 0.0002
load_in_4bit: false
load_in_8bit: false
local_rank: null
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_memory:
  0: 75GiB
max_steps: 30
micro_batch_size: 2
mlflow_experiment_name: /tmp/d37d23a80d00d27e_train_data.json
model_type: AutoModelForCausalLM
num_epochs: 1
optimizer: adamw_torch
output_dir: miner_id_24
pad_to_sequence_len: true
resume_from_checkpoint: null
s2_attention: null
sample_packing: false
save_steps: 10
sequence_len: 1024
special_tokens:
  pad_token: <|end_of_text|>
strict: false
tf32: false
tokenizer_type: AutoTokenizer
train_on_inputs: true
trust_remote_code: true
val_set_size: 0.05
wandb_entity: null
wandb_mode: online
wandb_name: fc3717cf-a3b8-4c1f-b267-52af07a02977
wandb_project: Gradients-On-Demand
wandb_run: your_name
wandb_runid: fc3717cf-a3b8-4c1f-b267-52af07a02977
warmup_steps: 10
weight_decay: 0.01
xformers_attention: true

```

</details><br>

# 8fd47b84-dd93-4a76-93c5-e9e7ae76c80f

This model is a fine-tuned version of [rayonlabs/merged-merged-af6dd40b-32e1-43b1-adfd-8ce14d65d738-PubMedQA-138437bf-44bd-4b03-8801-d05451a9ff28](https://huggingface.co./rayonlabs/merged-merged-af6dd40b-32e1-43b1-adfd-8ce14d65d738-PubMedQA-138437bf-44bd-4b03-8801-d05451a9ff28) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 1.4644

## 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_TORCH 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: 30

### Training results

| Training Loss | Epoch  | Step | Validation Loss |
|:-------------:|:------:|:----:|:---------------:|
| No log        | 0.0000 | 1    | 2.0503          |
| 2.0795        | 0.0003 | 8    | 1.6795          |
| 1.5127        | 0.0006 | 16   | 1.4891          |
| 1.4262        | 0.0010 | 24   | 1.4644          |


### Framework versions

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