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---
library_name: transformers
base_model: EleutherAI/pythia-14m
tags:
- axolotl
- generated_from_trainer
datasets:
- argilla/databricks-dolly-15k-curated-en
model-index:
- name: pythia-14m
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: `0.6.0`
```yaml
base_model: EleutherAI/pythia-14m
batch_size: 128
bf16: true
chat_template: tokenizer_default_fallback_alpaca
datasets:
- format: custom
path: argilla/databricks-dolly-15k-curated-en
type:
field_input: original-instruction
field_instruction: original-instruction
field_output: original-response
format: '{instruction} {input}'
no_input_format: '{instruction}'
system_format: '{system}'
system_prompt: ''
device_map: auto
eval_sample_packing: false
eval_steps: 20
flash_attention: true
gradient_checkpointing: true
group_by_length: true
hub_model_id: SystemAdmin123/pythia-14m
hub_strategy: checkpoint
learning_rate: 0.0002
logging_steps: 10
lr_scheduler: cosine
max_steps: 10000
micro_batch_size: 32
model_type: AutoModelForCausalLM
num_epochs: 100
optimizer: adamw_bnb_8bit
output_dir: /root/.sn56/axolotl/tmp/pythia-14m
pad_to_sequence_len: true
resize_token_embeddings_to_32x: false
sample_packing: true
save_steps: 20
save_total_limit: 1
sequence_len: 2048
special_tokens:
pad_token: <|endoftext|>
tokenizer_type: GPTNeoXTokenizerFast
torch_dtype: bf16
training_args_kwargs:
hub_private_repo: true
trust_remote_code: true
val_set_size: 0.1
wandb_entity: ''
wandb_mode: online
wandb_name: EleutherAI/pythia-14m-argilla/databricks-dolly-15k-curated-en
wandb_project: Gradients-On-Demand
wandb_run: your_name
wandb_runid: default
warmup_ratio: 0.05
```
</details><br>
# pythia-14m
This model is a fine-tuned version of [EleutherAI/pythia-14m](https://huggingface.co/EleutherAI/pythia-14m) on the argilla/databricks-dolly-15k-curated-en dataset.
It achieves the following results on the evaluation set:
- Loss: 8.8742
## 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: 32
- eval_batch_size: 32
- seed: 42
- distributed_type: multi-GPU
- num_devices: 4
- total_train_batch_size: 128
- total_eval_batch_size: 128
- 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: 5
- training_steps: 100
### Training results
| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-------:|:----:|:---------------:|
| No log | 0.1667 | 1 | 6.8294 |
| 10.057 | 3.3333 | 20 | 8.6254 |
| 9.7292 | 6.6667 | 40 | 8.7978 |
| 9.1399 | 10.0 | 60 | 8.8257 |
| 8.9523 | 13.3333 | 80 | 8.9145 |
| 8.9387 | 16.6667 | 100 | 8.8742 |
### Framework versions
- Transformers 4.48.1
- Pytorch 2.5.1+cu124
- Datasets 3.2.0
- Tokenizers 0.21.0
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