gpt-neo-1.3B-emailgen
This model is a fine-tuned version of EleutherAI/gpt-neo-1.3B on the postbot/multi-emails-100k dataset. It achieves the following results on the evaluation set:
- Loss: 1.6930
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: 0.0001
- train_batch_size: 4
- eval_batch_size: 4
- seed: 42
- distributed_type: multi-GPU
- gradient_accumulation_steps: 32
- total_train_batch_size: 128
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_ratio: 0.02
- num_epochs: 2
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 1.8669 | 1.0 | 789 | 1.7866 |
| 1.4049 | 2.0 | 1578 | 1.6930 |
Framework versions
- Transformers 4.22.2
- Pytorch 1.10.0+cu113
- Tokenizers 0.12.1
Open LLM Leaderboard Evaluation Results
Detailed results can be found here
| Metric | Value |
|---|---|
| Avg. | 33.47 |
| AI2 Reasoning Challenge (25-Shot) | 29.95 |
| HellaSwag (10-Shot) | 47.95 |
| MMLU (5-Shot) | 24.11 |
| TruthfulQA (0-shot) | 42.55 |
| Winogrande (5-shot) | 56.27 |
| GSM8k (5-shot) | 0.00 |