pythia-1.4b-sft-full
This model is a fine-tuned version of EleutherAI/pythia-1.4b on the HuggingFaceH4/ultrachat_200k dataset. It achieves the following results on the evaluation set:
- Loss: 1.3818
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: 2e-05
- train_batch_size: 12
- eval_batch_size: 8
- seed: 42
- distributed_type: multi-GPU
- num_devices: 4
- gradient_accumulation_steps: 2
- total_train_batch_size: 96
- total_eval_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 1
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 1.376 | 1.0 | 1335 | 1.3818 |
Framework versions
- Transformers 4.36.2
- Pytorch 2.2.1
- Datasets 2.14.6
- Tokenizers 0.15.2
Open LLM Leaderboard Evaluation Results
Detailed results can be found here
| Metric | Value |
|---|---|
| Avg. | 34.68 |
| AI2 Reasoning Challenge (25-Shot) | 32.68 |
| HellaSwag (10-Shot) | 52.08 |
| MMLU (5-Shot) | 25.44 |
| TruthfulQA (0-shot) | 38.42 |
| Winogrande (5-shot) | 57.46 |
| GSM8k (5-shot) | 1.97 |
- Downloads last month
- 7
This model does not have enough activity to be deployed to Inference API (serverless) yet. Increase its social
visibility and check back later, or deploy to Inference Endpoints (dedicated)
instead.
Model tree for nnheui/pythia-1.4b-sft-full
Base model
EleutherAI/pythia-1.4b