---
license: apache-2.0
base_model: t5-small
tags:
- generated_from_trainer
metrics:
- rouge
model-index:
- name: philosophy_model
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# philosophy_model

This model is a fine-tuned version of [t5-small](https://huggingface.co/t5-small) on a small manually curated dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0005
- Rouge1: 0.81
- Rouge2: 0.8004
- Rougel: 0.8107
- Rougelsum: 0.809
- Gen Len: 18.5

## Model description

This model summarises passages on Indian philosophy. 
Enter snippet from Hindu philosophy in text box on right. Click compute.

## Intended uses & limitations

More information needed

## Training and evaluation data

Dataset:130, train:100, test:30

## Training procedure

### Training hyperparameters

The following hyperparameters were used during training:
- learning_rate: 0.0056
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.99) and epsilon=1e-06
- lr_scheduler_type: linear
- num_epochs: 20

### Training results

| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|:-------:|
| No log        | 1.0   | 13   | 2.2462          | 0.3632 | 0.1462 | 0.3114 | 0.3126    | 18.3333 |
| No log        | 2.0   | 26   | 1.4611          | 0.459  | 0.3039 | 0.4178 | 0.4178    | 18.5667 |
| No log        | 3.0   | 39   | 0.8323          | 0.5465 | 0.4259 | 0.5247 | 0.5208    | 17.1333 |
| No log        | 4.0   | 52   | 0.4723          | 0.6161 | 0.5176 | 0.601  | 0.6004    | 18.3667 |
| No log        | 5.0   | 65   | 0.3121          | 0.6812 | 0.6078 | 0.6747 | 0.6714    | 18.2333 |
| No log        | 6.0   | 78   | 0.1546          | 0.7418 | 0.7023 | 0.7338 | 0.7313    | 18.0667 |
| No log        | 7.0   | 91   | 0.1121          | 0.7832 | 0.763  | 0.7802 | 0.7789    | 18.5    |
| No log        | 8.0   | 104  | 0.0699          | 0.8014 | 0.7882 | 0.8027 | 0.8009    | 18.5333 |
| No log        | 9.0   | 117  | 0.0459          | 0.7958 | 0.7805 | 0.7946 | 0.7917    | 18.5    |
| No log        | 10.0  | 130  | 0.0517          | 0.8091 | 0.7958 | 0.8105 | 0.809     | 18.4667 |
| No log        | 11.0  | 143  | 0.0358          | 0.7994 | 0.7852 | 0.7973 | 0.7946    | 18.5    |
| No log        | 12.0  | 156  | 0.0418          | 0.7799 | 0.7548 | 0.7747 | 0.7732    | 18.2667 |
| No log        | 13.0  | 169  | 0.0107          | 0.81   | 0.8004 | 0.8107 | 0.809     | 18.5    |
| No log        | 14.0  | 182  | 0.0065          | 0.8077 | 0.7971 | 0.8094 | 0.8075    | 18.5    |
| No log        | 15.0  | 195  | 0.0178          | 0.808  | 0.796  | 0.8094 | 0.8075    | 18.3667 |
| No log        | 16.0  | 208  | 0.0017          | 0.81   | 0.8004 | 0.8107 | 0.809     | 18.5    |
| No log        | 17.0  | 221  | 0.0055          | 0.81   | 0.8004 | 0.8107 | 0.809     | 18.5    |
| No log        | 18.0  | 234  | 0.0020          | 0.81   | 0.8004 | 0.8107 | 0.809     | 18.5    |
| No log        | 19.0  | 247  | 0.0006          | 0.81   | 0.8004 | 0.8107 | 0.809     | 18.5    |
| No log        | 20.0  | 260  | 0.0005          | 0.81   | 0.8004 | 0.8107 | 0.809     | 18.5    |


### Framework versions

- Transformers 4.33.2
- Pytorch 2.0.1+cu118
- Datasets 2.14.5
- Tokenizers 0.13.3