Transformers
TensorBoard
Safetensors
t5
text2text-generation
Generated from Trainer
text-generation-inference
Instructions to use BeenaSamuel/logs with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use BeenaSamuel/logs with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("BeenaSamuel/logs") model = AutoModelForSeq2SeqLM.from_pretrained("BeenaSamuel/logs", device_map="auto") - Notebooks
- Google Colab
- Kaggle
|
Download README.md from BeenaSamuel/logs: direct link, hf CLI and curl.
- Browser
- Download file 1.35 kB
-
https://huggingface.co/BeenaSamuel/logs/resolve/main/README.md
- Command line
-
hf download hf://BeenaSamuel/logs/README.md
-
curl -L -o README.md https://huggingface.co/BeenaSamuel/logs/resolve/main/README.md
1.35 kB
| license: apache-2.0 | |
| base_model: t5-small | |
| tags: | |
| - generated_from_trainer | |
| model-index: | |
| - name: logs | |
| 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. --> | |
| # logs | |
| This model is a fine-tuned version of [t5-small](https://huggingface.co/t5-small) on the None dataset. | |
| It achieves the following results on the evaluation set: | |
| - eval_loss: 0.3006 | |
| - eval_rouge1: 0.5924 | |
| - eval_rouge2: 0.326 | |
| - eval_rougeL: 0.5425 | |
| - eval_gen_len: 82.8793 | |
| - eval_runtime: 174.5683 | |
| - eval_samples_per_second: 6.124 | |
| - eval_steps_per_second: 0.768 | |
| - epoch: 2.79 | |
| - step: 1000 | |
| ## 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: 0.0001 | |
| - train_batch_size: 8 | |
| - eval_batch_size: 8 | |
| - seed: 42 | |
| - gradient_accumulation_steps: 8 | |
| - total_train_batch_size: 64 | |
| - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 | |
| - lr_scheduler_type: linear | |
| - lr_scheduler_warmup_steps: 500 | |
| - num_epochs: 5 | |
| ### Framework versions | |
| - Transformers 4.38.2 | |
| - Pytorch 2.1.2 | |
| - Datasets 2.1.0 | |
| - Tokenizers 0.15.2 | |