---
license: apache-2.0
base_model: t5-small
tags:
- generated_from_trainer
model-index:
- name: lesson-summarization
  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. -->

# lesson-summarization

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: 2.5713

## 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: 1
- eval_batch_size: 1
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 200

### Training results

| Training Loss | Epoch  | Step  | Validation Loss |
|:-------------:|:------:|:-----:|:---------------:|
| 2.9037        | 3.12   | 200   | 2.2456          |
| 2.5914        | 6.25   | 400   | 2.1498          |
| 2.393         | 9.38   | 600   | 2.1002          |
| 2.2409        | 12.5   | 800   | 2.0754          |
| 2.1515        | 15.62  | 1000  | 2.0683          |
| 2.0633        | 18.75  | 1200  | 2.0541          |
| 1.9418        | 21.88  | 1400  | 2.0603          |
| 1.837         | 25.0   | 1600  | 2.0788          |
| 1.7715        | 28.12  | 1800  | 2.0754          |
| 1.6957        | 31.25  | 2000  | 2.0815          |
| 1.6079        | 34.38  | 2200  | 2.0940          |
| 1.5947        | 37.5   | 2400  | 2.1094          |
| 1.4603        | 40.62  | 2600  | 2.1147          |
| 1.4621        | 43.75  | 2800  | 2.1354          |
| 1.4021        | 46.88  | 3000  | 2.1519          |
| 1.3394        | 50.0   | 3200  | 2.1670          |
| 1.2866        | 53.12  | 3400  | 2.1921          |
| 1.2681        | 56.25  | 3600  | 2.2045          |
| 1.1866        | 59.38  | 3800  | 2.2194          |
| 1.2098        | 62.5   | 4000  | 2.2302          |
| 1.1386        | 65.62  | 4200  | 2.2400          |
| 1.0853        | 68.75  | 4400  | 2.2634          |
| 1.0888        | 71.88  | 4600  | 2.2810          |
| 1.0408        | 75.0   | 4800  | 2.2909          |
| 1.0309        | 78.12  | 5000  | 2.3059          |
| 0.9523        | 81.25  | 5200  | 2.3249          |
| 0.9671        | 84.38  | 5400  | 2.3333          |
| 0.9413        | 87.5   | 5600  | 2.3543          |
| 0.9127        | 90.62  | 5800  | 2.3636          |
| 0.9095        | 93.75  | 6000  | 2.3676          |
| 0.8952        | 96.88  | 6200  | 2.3756          |
| 0.857         | 100.0  | 6400  | 2.3878          |
| 0.8474        | 103.12 | 6600  | 2.4148          |
| 0.8215        | 106.25 | 6800  | 2.4231          |
| 0.8172        | 109.38 | 7000  | 2.4243          |
| 0.7761        | 112.5  | 7200  | 2.4489          |
| 0.7737        | 115.62 | 7400  | 2.4718          |
| 0.7476        | 118.75 | 7600  | 2.4614          |
| 0.7345        | 121.88 | 7800  | 2.4705          |
| 0.7426        | 125.0  | 8000  | 2.4740          |
| 0.7151        | 128.12 | 8200  | 2.4833          |
| 0.7191        | 131.25 | 8400  | 2.4786          |
| 0.6818        | 134.38 | 8600  | 2.4882          |
| 0.6862        | 137.5  | 8800  | 2.4938          |
| 0.6929        | 140.62 | 9000  | 2.4977          |
| 0.6494        | 143.75 | 9200  | 2.5195          |
| 0.6689        | 146.88 | 9400  | 2.5185          |
| 0.6492        | 150.0  | 9600  | 2.5259          |
| 0.6384        | 153.12 | 9800  | 2.5259          |
| 0.6435        | 156.25 | 10000 | 2.5287          |
| 0.6251        | 159.38 | 10200 | 2.5284          |
| 0.6295        | 162.5  | 10400 | 2.5398          |
| 0.6324        | 165.62 | 10600 | 2.5442          |
| 0.6252        | 168.75 | 10800 | 2.5481          |
| 0.6108        | 171.88 | 11000 | 2.5455          |
| 0.6034        | 175.0  | 11200 | 2.5502          |
| 0.5969        | 178.12 | 11400 | 2.5601          |
| 0.5949        | 181.25 | 11600 | 2.5617          |
| 0.6183        | 184.38 | 11800 | 2.5679          |
| 0.5805        | 187.5  | 12000 | 2.5687          |
| 0.6032        | 190.62 | 12200 | 2.5708          |
| 0.5955        | 193.75 | 12400 | 2.5709          |
| 0.5961        | 196.88 | 12600 | 2.5713          |
| 0.5914        | 200.0  | 12800 | 2.5713          |


### Framework versions

- Transformers 4.31.0
- Pytorch 1.13.1
- Datasets 2.12.0
- Tokenizers 0.13.3