Summarization
Transformers
Safetensors
t5
text2text-generation
Generated from Trainer
text-generation-inference
Instructions to use anonymous813ker/summary-generator-128 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use anonymous813ker/summary-generator-128 with Transformers:
# Use a pipeline as a high-level helper # Warning: Pipeline type "summarization" is no longer supported in transformers v5. # You must load the model directly (see below) or downgrade to v4.x with: # 'pip install "transformers<5.0.0' from transformers import pipeline pipe = pipeline("summarization", model="anonymous813ker/summary-generator-128")# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("anonymous813ker/summary-generator-128") model = AutoModelForSeq2SeqLM.from_pretrained("anonymous813ker/summary-generator-128") - Notebooks
- Google Colab
- Kaggle
summary-generator-128
This model is a fine-tuned version of google-t5/t5-small on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 1.6233
- Rouge1: 0.523
- Rouge2: 0.3181
- Rougel: 0.4115
- Rougelsum: 0.4115
- Gen Len: 119.4524
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: 32
- eval_batch_size: 32
- 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: 4
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
|---|---|---|---|---|---|---|---|---|
| 2.2692 | 1.0 | 593 | 1.7477 | 0.5022 | 0.2954 | 0.3899 | 0.3899 | 113.4738 |
| 1.9395 | 2.0 | 1186 | 1.6635 | 0.5177 | 0.3112 | 0.4046 | 0.4045 | 117.821 |
| 1.8828 | 3.0 | 1779 | 1.6317 | 0.5221 | 0.3166 | 0.41 | 0.41 | 119.5176 |
| 1.8478 | 4.0 | 2372 | 1.6233 | 0.523 | 0.3181 | 0.4115 | 0.4115 | 119.4524 |
Framework versions
- Transformers 5.8.1
- Pytorch 2.5.1
- Datasets 4.8.5
- Tokenizers 0.22.2
- Downloads last month
- 64
Model tree for anonymous813ker/summary-generator-128
Base model
google-t5/t5-small