Text Generation
Transformers
TensorBoard
Safetensors
gpt2
Generated from Trainer
text-generation-inference
# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM
tokenizer = AutoTokenizer.from_pretrained("Stiron/codeparrot-ds")
model = AutoModelForCausalLM.from_pretrained("Stiron/codeparrot-ds")Quick Links
codeparrot-ds
This model is a fine-tuned version of gpt2 on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 5.1291
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: 0.0005
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- gradient_accumulation_steps: 8
- total_train_batch_size: 256
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_steps: 10
- num_epochs: 5
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 9.5166 | 0.2332 | 10 | 7.9560 |
| 7.161 | 0.4665 | 20 | 6.8948 |
| 6.7973 | 0.6997 | 30 | 6.7108 |
| 6.4652 | 0.9329 | 40 | 6.3878 |
| 6.1192 | 1.1662 | 50 | 6.1154 |
| 5.842 | 1.3994 | 60 | 5.8976 |
| 5.6262 | 1.6327 | 70 | 5.7493 |
| 5.4633 | 1.8659 | 80 | 5.6221 |
| 5.3212 | 2.0991 | 90 | 5.5376 |
| 5.1513 | 2.3324 | 100 | 5.4584 |
| 5.118 | 2.5656 | 110 | 5.3924 |
| 4.9714 | 2.7988 | 120 | 5.3301 |
| 4.9133 | 3.0321 | 130 | 5.2827 |
| 4.7702 | 3.2653 | 140 | 5.2460 |
| 4.7302 | 3.4985 | 150 | 5.2081 |
| 4.6988 | 3.7318 | 160 | 5.1740 |
| 4.6927 | 3.9650 | 170 | 5.1537 |
| 4.6044 | 4.1983 | 180 | 5.1442 |
| 4.5763 | 4.4315 | 190 | 5.1361 |
| 4.5913 | 4.6647 | 200 | 5.1298 |
| 4.5759 | 4.8980 | 210 | 5.1291 |
Framework versions
- Transformers 4.41.2
- Pytorch 2.3.0+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1
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Model tree for Stiron/codeparrot-ds
Base model
openai-community/gpt2
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="Stiron/codeparrot-ds")