Token Classification
Transformers
TensorBoard
Safetensors
gpt2
Generated from Trainer
text-generation-inference
# Load model directly
from transformers import AutoTokenizer, AutoModelForTokenClassification
tokenizer = AutoTokenizer.from_pretrained("Irisissocute/results")
model = AutoModelForTokenClassification.from_pretrained("Irisissocute/results")Quick Links
results
This model is a fine-tuned version of microsoft/biogpt on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.1458
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: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| No log | 1.0 | 340 | 0.1963 |
| 0.2426 | 2.0 | 680 | 0.1614 |
| 0.1198 | 3.0 | 1020 | 0.1458 |
Framework versions
- Transformers 4.39.3
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2
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Model tree for Irisissocute/results
Base model
microsoft/biogpt
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="Irisissocute/results")