Transformers
TensorBoard
Safetensors
t5
text2text-generation
Generated from Trainer
text-generation-inference
Instructions to use karthiksab/new_summary_model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use karthiksab/new_summary_model with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("karthiksab/new_summary_model") model = AutoModelForSeq2SeqLM.from_pretrained("karthiksab/new_summary_model") - Notebooks
- Google Colab
- Kaggle
new_summary_model
This model is a fine-tuned version of t5-small on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 1.4928
- Rouge1: 0.22
- Rouge2: 0.09
- Rougel: 0.18
- Rougelsum: 0.18
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
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum |
|---|---|---|---|---|---|---|---|
| 1.7131 | 1.0 | 1615 | 1.5056 | 0.21 | 0.09 | 0.18 | 0.18 |
| 1.7014 | 2.0 | 3230 | 1.4948 | 0.21 | 0.09 | 0.18 | 0.18 |
| 1.6827 | 3.0 | 4845 | 1.4928 | 0.22 | 0.09 | 0.18 | 0.18 |
Framework versions
- Transformers 4.38.2
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2
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Base model
google-t5/t5-small