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# billsum_tiny_summarization

This model is a fine-tuned version of [google/t5-efficient-tiny](https://huggingface.co/google/t5-efficient-tiny) on the billsum dataset.
It achieves the following results on the evaluation set:
- Loss: 3.5889
- Rouge1: 0.1503
- Rouge2: 0.0412
- Rougel: 0.1244
- Rougelsum: 0.1244
- Gen Len: 19.0

## 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: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 4

### Training results

| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|:-------:|
| No log        | 1.0   | 62   | 4.2835          | 0.1413 | 0.0323 | 0.1125 | 0.1124    | 19.0    |
| No log        | 2.0   | 124  | 3.7275          | 0.1507 | 0.0408 | 0.1263 | 0.1264    | 19.0    |
| No log        | 3.0   | 186  | 3.6154          | 0.1499 | 0.0407 | 0.1244 | 0.1244    | 19.0    |
| No log        | 4.0   | 248  | 3.5889          | 0.1503 | 0.0412 | 0.1244 | 0.1244    | 19.0    |


### Framework versions

- Transformers 4.33.3
- Pytorch 2.0.1+cu118
- Datasets 2.14.5
- Tokenizers 0.13.3
{"license": "apache-2.0", "tags": ["generated_from_trainer"], "datasets": ["billsum"], "metrics": ["rouge"], "base_model": "google/t5-efficient-tiny", "pipeline_tag": "summarization", "model-index": [{"name": "billsum_tiny_summarization", "results": [{"task": {"type": "summarization", "name": "Sequence-to-sequence Language Modeling"}, "dataset": {"name": "billsum", "type": "billsum", "config": "default", "split": "ca_test", "args": "default"}, "metrics": [{"type": "rouge", "value": 0.1503, "name": "Rouge1"}]}]}]}
transformers pytorch t5 text2text-generation generated_from_trainer summarization dataset:billsum base_model:google/t5-efficient-tiny license:apache-2.0 model-index autotrain_compatible endpoints_compatible has_space text-generation-inference region:us