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# t5-summarization-one-shot-better-prompt

This model is a fine-tuned version of [google/flan-t5-small](https://huggingface.co/google/flan-t5-small) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 2.2431
- Rouge: {'rouge1': 39.1164, 'rouge2': 19.0784, 'rougeL': 20.2856, 'rougeLsum': 20.2856}
- Bert Score: 0.8802
- Bleurt 20: -0.7688
- Gen Len: 13.545

## 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: 7
- eval_batch_size: 7
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 20

### Training results

| Training Loss | Epoch | Step | Validation Loss | Rouge                                                                           | Bert Score | Bleurt 20 | Gen Len |
|:-------------:|:-----:|:----:|:---------------:|:-------------------------------------------------------------------------------:|:----------:|:---------:|:-------:|
| 2.6921        | 1.0   | 172  | 2.4379          | {'rouge1': 43.7984, 'rouge2': 17.2952, 'rougeL': 18.5604, 'rougeLsum': 18.5604} | 0.869      | -0.8739   | 14.84   |
| 2.5119        | 2.0   | 344  | 2.3282          | {'rouge1': 41.5219, 'rouge2': 17.4612, 'rougeL': 19.5103, 'rougeLsum': 19.5103} | 0.8749     | -0.8329   | 13.7    |
| 2.3033        | 3.0   | 516  | 2.2821          | {'rouge1': 41.0636, 'rouge2': 18.2347, 'rougeL': 19.8704, 'rougeLsum': 19.8704} | 0.878      | -0.8268   | 13.75   |
| 2.2139        | 4.0   | 688  | 2.2404          | {'rouge1': 39.9679, 'rouge2': 18.8795, 'rougeL': 19.7032, 'rougeLsum': 19.7032} | 0.8796     | -0.8035   | 13.305  |
| 2.0835        | 5.0   | 860  | 2.2446          | {'rouge1': 41.8958, 'rouge2': 18.439, 'rougeL': 19.2982, 'rougeLsum': 19.2982}  | 0.877      | -0.7963   | 14.34   |
| 2.0379        | 6.0   | 1032 | 2.2233          | {'rouge1': 40.9703, 'rouge2': 19.7574, 'rougeL': 19.9387, 'rougeLsum': 19.9387} | 0.8793     | -0.7805   | 13.625  |
| 1.959         | 7.0   | 1204 | 2.2073          | {'rouge1': 39.2194, 'rouge2': 18.9553, 'rougeL': 19.7847, 'rougeLsum': 19.7847} | 0.8787     | -0.8045   | 13.365  |
| 1.9177        | 8.0   | 1376 | 2.2146          | {'rouge1': 40.8391, 'rouge2': 19.5219, 'rougeL': 20.2602, 'rougeLsum': 20.2602} | 0.8781     | -0.7974   | 13.865  |
| 1.8749        | 9.0   | 1548 | 2.2071          | {'rouge1': 40.9497, 'rouge2': 19.9867, 'rougeL': 20.5682, 'rougeLsum': 20.5682} | 0.8808     | -0.7812   | 13.68   |
| 1.8112        | 10.0  | 1720 | 2.2045          | {'rouge1': 36.465, 'rouge2': 16.4287, 'rougeL': 19.1978, 'rougeLsum': 19.1978}  | 0.8772     | -0.8384   | 13.295  |
| 1.7475        | 11.0  | 1892 | 2.2210          | {'rouge1': 39.4889, 'rouge2': 19.1309, 'rougeL': 19.879, 'rougeLsum': 19.879}   | 0.8785     | -0.8074   | 13.585  |
| 1.7384        | 12.0  | 2064 | 2.2269          | {'rouge1': 38.2904, 'rouge2': 18.2873, 'rougeL': 19.4418, 'rougeLsum': 19.4418} | 0.8789     | -0.7984   | 13.42   |
| 1.6849        | 13.0  | 2236 | 2.2261          | {'rouge1': 37.6283, 'rouge2': 17.6979, 'rougeL': 19.584, 'rougeLsum': 19.584}   | 0.878      | -0.7885   | 13.445  |
| 1.6531        | 14.0  | 2408 | 2.2186          | {'rouge1': 38.7975, 'rouge2': 19.0939, 'rougeL': 20.7873, 'rougeLsum': 20.7873} | 0.8806     | -0.783    | 13.445  |
| 1.663         | 15.0  | 2580 | 2.2245          | {'rouge1': 38.9159, 'rouge2': 19.153, 'rougeL': 20.5232, 'rougeLsum': 20.5232}  | 0.8811     | -0.7514   | 13.59   |
| 1.6036        | 16.0  | 2752 | 2.2430          | {'rouge1': 37.6184, 'rouge2': 17.6773, 'rougeL': 19.2693, 'rougeLsum': 19.2693} | 0.8771     | -0.7992   | 13.6    |
| 1.6333        | 17.0  | 2924 | 2.2418          | {'rouge1': 38.1301, 'rouge2': 18.4061, 'rougeL': 20.1355, 'rougeLsum': 20.1355} | 0.879      | -0.7845   | 13.49   |
| 1.6322        | 18.0  | 3096 | 2.2421          | {'rouge1': 38.0746, 'rouge2': 18.2039, 'rougeL': 19.7404, 'rougeLsum': 19.7404} | 0.8789     | -0.7892   | 13.41   |
| 1.5982        | 19.0  | 3268 | 2.2411          | {'rouge1': 39.1375, 'rouge2': 19.1696, 'rougeL': 20.2695, 'rougeLsum': 20.2695} | 0.8802     | -0.7713   | 13.465  |
| 1.593         | 20.0  | 3440 | 2.2431          | {'rouge1': 39.1164, 'rouge2': 19.0784, 'rougeL': 20.2856, 'rougeLsum': 20.2856} | 0.8802     | -0.7688   | 13.545  |


### Framework versions

- Transformers 4.35.2
- Pytorch 2.1.0+cu121
- Datasets 2.16.1
- Tokenizers 0.15.0

{"license": "apache-2.0", "tags": ["generated_from_trainer"], "metrics": ["rouge"], "base_model": "google/flan-t5-small", "model-index": [{"name": "t5-summarization-one-shot-better-prompt", "results": []}]}
transformers tensorboard safetensors t5 text2text-generation generated_from_trainer base_model:google/flan-t5-small license:apache-2.0 autotrain_compatible endpoints_compatible text-generation-inference region:us