Summarization
Transformers
TensorBoard
Safetensors
mt5
text2text-generation
Generated from Trainer
Eval Results (legacy)
# Load model directly
from transformers import AutoTokenizer, AutoModelForSeq2SeqLM
tokenizer = AutoTokenizer.from_pretrained("Ah7med/mt5-small-finetuned")
model = AutoModelForSeq2SeqLM.from_pretrained("Ah7med/mt5-small-finetuned")Quick Links
mt5-small-finetuned
This model is a fine-tuned version of google/mt5-small on the samsum dataset. It achieves the following results on the evaluation set:
- Loss: 1.7974
- Rouge1: 0.4303
- Rouge2: 0.2038
- Rougel: 0.3736
- Rougelsum: 0.3734
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: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Use 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: 8
Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum |
|---|---|---|---|---|---|---|---|
| 2.1585 | 1.0 | 1842 | 1.9205 | 0.4074 | 0.1838 | 0.3517 | 0.3518 |
| 2.1545 | 2.0 | 3684 | 1.8882 | 0.4120 | 0.1914 | 0.3592 | 0.3588 |
| 2.0888 | 3.0 | 5526 | 1.8290 | 0.4196 | 0.1939 | 0.3603 | 0.3601 |
| 2.0272 | 4.0 | 7368 | 1.8269 | 0.4215 | 0.1975 | 0.3637 | 0.3635 |
| 1.9871 | 5.0 | 9210 | 1.8224 | 0.4231 | 0.1943 | 0.3634 | 0.3633 |
| 1.9535 | 6.0 | 11052 | 1.8055 | 0.4285 | 0.2030 | 0.3715 | 0.3715 |
| 1.9322 | 7.0 | 12894 | 1.7954 | 0.4270 | 0.2018 | 0.3698 | 0.3697 |
| 1.9181 | 8.0 | 14736 | 1.7974 | 0.4303 | 0.2038 | 0.3736 | 0.3734 |
Framework versions
- Transformers 4.47.0
- Pytorch 2.5.1+cu121
- Datasets 3.2.0
- Tokenizers 0.21.0
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Model tree for Ah7med/mt5-small-finetuned
Base model
google/mt5-smallEvaluation results
- Rouge1 on samsumvalidation set self-reported0.430
# 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="Ah7med/mt5-small-finetuned")