---
license: apache-2.0
base_model: t5-small
tags:
- generated_from_trainer
metrics:
- rouge
model-index:
- name: t5-small-finetuned-manimml-1.1
  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. -->

# t5-small-finetuned-manimml-1.1

This model is a fine-tuned version of [t5-small](https://huggingface.co/t5-small) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0750
- Rouge1: 26.2677
- Rouge2: 21.24
- Rougel: 26.2649
- Rougelsum: 26.2291
- 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: 15
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Rouge1  | Rouge2  | Rougel  | Rougelsum | Gen Len |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:|:-------:|:---------:|:-------:|
| No log        | 1.0   | 50   | 1.6688          | 4.48    | 0.3941  | 4.3103  | 4.3263    | 19.0    |
| No log        | 2.0   | 100  | 0.8312          | 11.3557 | 2.7306  | 10.6554 | 10.6787   | 18.985  |
| No log        | 3.0   | 150  | 0.4371          | 24.1056 | 14.6464 | 23.4038 | 23.3396   | 19.0    |
| No log        | 4.0   | 200  | 0.2658          | 26.1867 | 17.1716 | 25.6324 | 25.5875   | 19.0    |
| No log        | 5.0   | 250  | 0.1862          | 25.7525 | 18.2023 | 25.3068 | 25.2656   | 19.0    |
| No log        | 6.0   | 300  | 0.1429          | 26.1909 | 19.8811 | 26.0053 | 26.0106   | 19.0    |
| No log        | 7.0   | 350  | 0.1180          | 26.1977 | 20.6534 | 26.1067 | 26.0828   | 19.0    |
| No log        | 8.0   | 400  | 0.1055          | 26.0723 | 21.0154 | 26.0943 | 26.0582   | 19.0    |
| No log        | 9.0   | 450  | 0.0934          | 26.2485 | 21.1998 | 26.2506 | 26.2173   | 19.0    |
| 0.8503        | 10.0  | 500  | 0.0863          | 26.2677 | 21.24   | 26.2649 | 26.2291   | 19.0    |
| 0.8503        | 11.0  | 550  | 0.0819          | 26.2677 | 21.24   | 26.2649 | 26.2291   | 19.0    |
| 0.8503        | 12.0  | 600  | 0.0795          | 26.2677 | 21.24   | 26.2649 | 26.2291   | 19.0    |
| 0.8503        | 13.0  | 650  | 0.0768          | 26.2677 | 21.24   | 26.2649 | 26.2291   | 19.0    |
| 0.8503        | 14.0  | 700  | 0.0755          | 26.2677 | 21.24   | 26.2649 | 26.2291   | 19.0    |
| 0.8503        | 15.0  | 750  | 0.0750          | 26.2677 | 21.24   | 26.2649 | 26.2291   | 19.0    |


### Framework versions

- Transformers 4.41.2
- Pytorch 2.3.0+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1