# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM
tokenizer = AutoTokenizer.from_pretrained("osanseviero/sft_cml4")
model = AutoModelForCausalLM.from_pretrained("osanseviero/sft_cml4")Quick Links
sft_cml4
This model is a fine-tuned version of gpt2 on the ag_news dataset. It achieves the following results on the evaluation set:
- Loss: 3.3980
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: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- num_epochs: 2
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 3.7271 | 0.32 | 200 | 3.6065 |
| 3.346 | 0.64 | 400 | 3.4732 |
| 3.0685 | 0.96 | 600 | 3.3985 |
| 2.1435 | 1.28 | 800 | 3.4433 |
| 1.9834 | 1.6 | 1000 | 3.4203 |
| 1.8937 | 1.92 | 1200 | 3.3980 |
Framework versions
- Transformers 4.34.1
- Pytorch 2.0.1+cu118
- Datasets 2.14.4
- Tokenizers 0.14.0
- Downloads last month
- 5
Model tree for osanseviero/sft_cml4
Base model
openai-community/gpt2
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="osanseviero/sft_cml4")