Instructions to use amin-oj/mt5-small-finetuned-summarization-amazon_reviews_multi with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use amin-oj/mt5-small-finetuned-summarization-amazon_reviews_multi 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="amin-oj/mt5-small-finetuned-summarization-amazon_reviews_multi")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("amin-oj/mt5-small-finetuned-summarization-amazon_reviews_multi") model = AutoModelForSeq2SeqLM.from_pretrained("amin-oj/mt5-small-finetuned-summarization-amazon_reviews_multi", device_map="auto") - Notebooks
- Google Colab
- Kaggle
mt5-small-finetuned-summarization-amazon_reviews_multi
This model is a fine-tuned version of google/mt5-small on the None dataset. It achieves the following results on the evaluation set:
- Loss: 3.4018
- Rouge1: 9.9985
- Rouge2: 2.8179
- Rougel: 9.7638
- Rougelsum: 9.8649
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: 5.6e-05
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 4
Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum |
|---|---|---|---|---|---|---|---|
| No log | 1.0 | 153 | 5.7761 | 3.6167 | 1.1182 | 3.4522 | 3.473 |
| 20.5610 | 2.0 | 306 | 4.0384 | 8.7252 | 2.8086 | 8.5396 | 8.6162 |
| 20.5610 | 3.0 | 459 | 3.5351 | 9.6513 | 2.4522 | 9.4417 | 9.5315 |
| 10.3854 | 4.0 | 612 | 3.4018 | 9.9985 | 2.8179 | 9.7638 | 9.8649 |
Framework versions
- Transformers 5.0.0
- Pytorch 2.10.0+cu128
- Datasets 4.8.3
- Tokenizers 0.22.2
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Model tree for amin-oj/mt5-small-finetuned-summarization-amazon_reviews_multi
Base model
google/mt5-small