# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM
tokenizer = AutoTokenizer.from_pretrained("sam-fsm/gpt2-on-squad")
model = AutoModelForCausalLM.from_pretrained("sam-fsm/gpt2-on-squad")Quick Links
sam-fsm/gpt2-finetuned-wikitext2
This model is a fine-tuned version of gpt2 on an unknown dataset. It achieves the following results on the evaluation set:
- Train Loss: 6.1287
- Validation Loss: 5.6521
- Epoch: 0
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:
- optimizer: {'name': 'AdamWeightDecay', 'learning_rate': 2e-05, 'decay': 0.0, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-07, 'amsgrad': False, 'weight_decay_rate': 0.01}
- training_precision: float32
Training results
| Train Loss | Validation Loss | Epoch |
|---|---|---|
| 6.1287 | 5.6521 | 0 |
Framework versions
- Transformers 4.31.0
- TensorFlow 2.12.0
- Datasets 2.14.1
- Tokenizers 0.13.3
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Model tree for sam-fsm/gpt2-on-squad
Base model
openai-community/gpt2
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="sam-fsm/gpt2-on-squad")