Transformers
PyTorch
TensorBoard
Safetensors
t5
text2text-generation
Generated from Trainer
text-generation-inference
Instructions to use peterbeamish/trained_model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use peterbeamish/trained_model with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("peterbeamish/trained_model") model = AutoModelForSeq2SeqLM.from_pretrained("peterbeamish/trained_model") - Notebooks
- Google Colab
- Kaggle
| license: apache-2.0 | |
| base_model: google/flan-t5-large | |
| tags: | |
| - generated_from_trainer | |
| model-index: | |
| - name: trained_model | |
| results: [] | |
| <!-- This model card has been generated automatically according to the information the Trainer had access to. You | |
| should probably proofread and complete it, then remove this comment. --> | |
| # trained_model | |
| This model is a fine-tuned version of [google/flan-t5-large](https://huggingface.co/google/flan-t5-large) on an unknown dataset. | |
| ## 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: 0.00023571124327298023 | |
| - train_batch_size: 60 | |
| - eval_batch_size: 8 | |
| - seed: 42 | |
| - gradient_accumulation_steps: 5 | |
| - total_train_batch_size: 300 | |
| - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 | |
| - lr_scheduler_type: linear | |
| - num_epochs: 4 | |
| ### Training results | |
| | Training Loss | Epoch | Step | Validation Loss | | |
| |:-------------:|:-----:|:----:|:---------------:| | |
| | No log | 2.79 | 100 | 1.1187 | | |
| ### Framework versions | |
| - Transformers 4.35.0 | |
| - Pytorch 2.1.0+cu118 | |
| - Datasets 2.14.6 | |
| - Tokenizers 0.14.1 | |