testflant5
This model is a fine-tuned version of google/flan-t5-base on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 1.3889
- Bertscore F1: 89.8552
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: 5e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 5
Training results
| Training Loss | Epoch | Step | Validation Loss | Bertscore F1 |
|---|---|---|---|---|
| No log | 1.0 | 2 | 1.7088 | 88.56 |
| No log | 2.0 | 4 | 1.6045 | 89.2892 |
| No log | 3.0 | 6 | 1.4956 | 89.1683 |
| No log | 4.0 | 8 | 1.4173 | 88.9652 |
| No log | 5.0 | 10 | 1.3889 | 89.8552 |
Framework versions
- Transformers 4.49.0
- Pytorch 2.5.1+cu124
- Datasets 3.3.1
- Tokenizers 0.21.0
- Downloads last month
- 1
Inference Providers NEW
This model isn't deployed by any Inference Provider. 🙋 Ask for provider support
Model tree for ckrouch/testflant5
Base model
google/flan-t5-base
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("ckrouch/testflant5") model = AutoModelForSeq2SeqLM.from_pretrained("ckrouch/testflant5", device_map="auto")