transformers safetensors t5 text2text-generation generated_from_trainer base_model:google/flan-t5-large license:apache-2.0 autotrain_compatible endpoints_compatible text-generation-inference region:us
---
license: apache-2.0
base_model: google/flan-t5-large
tags:
- generated_from_trainer
metrics:
- rouge
model-index:
- name: flan-t5-large-mawpnli-calcx-nli-pt
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->

# flan-t5-large-mawpnli-calcx-nli-pt

This model is a fine-tuned version of [google/flan-t5-large](https://huggingface.co/google/flan-t5-large) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1217
- Rouge1: 95.7098
- Rouge2: 89.9271
- Rougel: 95.5836
- Rougelsum: 95.5842
- Gen Len: 10.9151

## 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: 5e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5

### Training results

| Training Loss | Epoch | Step | Validation Loss | Rouge1  | Rouge2  | Rougel  | Rougelsum | Gen Len |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:|:-------:|:---------:|:-------:|
| 0.2279        | 1.0   | 819  | 0.1290          | 95.075  | 87.8764 | 94.7902 | 94.8057   | 10.7978 |
| 0.0612        | 2.0   | 1638 | 0.1012          | 95.6219 | 89.6809 | 95.4399 | 95.4521   | 10.9029 |
| 0.0418        | 3.0   | 2457 | 0.0972          | 95.7709 | 90.1703 | 95.613  | 95.637    | 10.9328 |
| 0.0272        | 4.0   | 3276 | 0.1174          | 95.7478 | 90.1332 | 95.5931 | 95.6069   | 10.9395 |
| 0.0215        | 5.0   | 4095 | 0.1217          | 95.7098 | 89.9271 | 95.5836 | 95.5842   | 10.9151 |


### Framework versions

- Transformers 4.35.2
- Pytorch 1.12.1+cu113
- Datasets 2.15.0
- Tokenizers 0.15.0
