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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: 2.3104
- Rouge: {'rouge1': 43.2304, 'rouge2': 20.0106, 'rougeL': 19.6358, 'rougeLsum': 19.6358}
- Bert Score: 0.8771
- Bleurt 20: -0.8213
- Gen Len: 13.765

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:-------------------------------------------------------------------------------:|:----------:|:---------:|:-------:|
| 2.6246        | 1.0   | 172  | 2.4757          | {'rouge1': 44.9153, 'rouge2': 18.5718, 'rougeL': 19.4145, 'rougeLsum': 19.4145} | 0.8727     | -0.8454   | 14.15   |
| 2.4225        | 2.0   | 344  | 2.3819          | {'rouge1': 43.3173, 'rouge2': 18.3383, 'rougeL': 18.49, 'rougeLsum': 18.49}     | 0.87       | -0.8976   | 13.895  |
| 2.2187        | 3.0   | 516  | 2.3301          | {'rouge1': 40.6109, 'rouge2': 16.9766, 'rougeL': 18.1673, 'rougeLsum': 18.1673} | 0.8703     | -0.9236   | 13.47   |
| 2.1314        | 4.0   | 688  | 2.2950          | {'rouge1': 43.6761, 'rouge2': 18.7232, 'rougeL': 18.9003, 'rougeLsum': 18.9003} | 0.8726     | -0.8971   | 14.095  |
| 1.9971        | 5.0   | 860  | 2.2897          | {'rouge1': 42.3985, 'rouge2': 18.5244, 'rougeL': 18.5991, 'rougeLsum': 18.5991} | 0.8719     | -0.9075   | 13.585  |
| 1.9511        | 6.0   | 1032 | 2.2926          | {'rouge1': 42.4732, 'rouge2': 18.4346, 'rougeL': 19.0653, 'rougeLsum': 19.0653} | 0.8767     | -0.8847   | 13.45   |
| 1.8624        | 7.0   | 1204 | 2.2883          | {'rouge1': 41.6345, 'rouge2': 18.3464, 'rougeL': 19.0603, 'rougeLsum': 19.0603} | 0.8767     | -0.8899   | 13.21   |
| 1.8361        | 8.0   | 1376 | 2.2816          | {'rouge1': 44.2794, 'rouge2': 19.6559, 'rougeL': 19.7029, 'rougeLsum': 19.7029} | 0.8767     | -0.8561   | 14.045  |
| 1.7869        | 9.0   | 1548 | 2.2807          | {'rouge1': 43.4703, 'rouge2': 18.9051, 'rougeL': 19.5826, 'rougeLsum': 19.5826} | 0.8781     | -0.8442   | 13.82   |
| 1.7048        | 10.0  | 1720 | 2.2624          | {'rouge1': 42.8553, 'rouge2': 18.5641, 'rougeL': 19.3523, 'rougeLsum': 19.3523} | 0.8769     | -0.8679   | 13.665  |
| 1.6718        | 11.0  | 1892 | 2.2757          | {'rouge1': 43.1539, 'rouge2': 19.3463, 'rougeL': 19.8968, 'rougeLsum': 19.8968} | 0.8783     | -0.8662   | 13.61   |
| 1.6599        | 12.0  | 2064 | 2.2909          | {'rouge1': 43.5918, 'rouge2': 19.7046, 'rougeL': 19.673, 'rougeLsum': 19.673}   | 0.8767     | -0.8587   | 13.79   |
| 1.5895        | 13.0  | 2236 | 2.2927          | {'rouge1': 43.787, 'rouge2': 20.2026, 'rougeL': 19.8817, 'rougeLsum': 19.8817}  | 0.878      | -0.8296   | 13.95   |
| 1.5527        | 14.0  | 2408 | 2.2987          | {'rouge1': 43.3703, 'rouge2': 19.6301, 'rougeL': 19.8362, 'rougeLsum': 19.8362} | 0.8776     | -0.8473   | 13.635  |
| 1.5892        | 15.0  | 2580 | 2.2942          | {'rouge1': 43.3245, 'rouge2': 19.7414, 'rougeL': 19.7625, 'rougeLsum': 19.7625} | 0.8772     | -0.8295   | 13.805  |
| 1.5273        | 16.0  | 2752 | 2.3007          | {'rouge1': 43.0611, 'rouge2': 19.8572, 'rougeL': 19.7198, 'rougeLsum': 19.7198} | 0.877      | -0.8293   | 13.795  |
| 1.5546        | 17.0  | 2924 | 2.3019          | {'rouge1': 43.1098, 'rouge2': 19.699, 'rougeL': 19.8258, 'rougeLsum': 19.8258}  | 0.8763     | -0.841    | 13.785  |
| 1.5363        | 18.0  | 3096 | 2.3070          | {'rouge1': 43.9332, 'rouge2': 20.1972, 'rougeL': 19.8764, 'rougeLsum': 19.8764} | 0.878      | -0.8167   | 13.86   |
| 1.5118        | 19.0  | 3268 | 2.3105          | {'rouge1': 43.2268, 'rouge2': 20.074, 'rougeL': 19.831, 'rougeLsum': 19.831}    | 0.8778     | -0.8134   | 13.78   |
| 1.502         | 20.0  | 3440 | 2.3104          | {'rouge1': 43.2304, 'rouge2': 20.0106, 'rougeL': 19.6358, 'rougeLsum': 19.6358} | 0.8771     | -0.8213   | 13.765  |


### 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