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
- 16
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.