---
base_model: EleutherAI/pile-t5-base
tags:
- generated_from_trainer
model-index:
- name: pile-t5-base-inst
  results: []
language:
- en
metrics:
- rouge
library_name: transformers
---

<!-- 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. -->

# pile-t5-base-inst

This model is a fine-tuned version of [EleutherAI/pile-t5-base](https://huggingface.co/EleutherAI/pile-t5-base) on [taskydata/Pile-T5-Instruction](https://huggingface.co/datasets/taskydata/Pile-T5-Instruction) dataset.
It achieves the following results on the evaluation set:
- Loss: 2.5082
- Rouge2 Precision: 0.2496
- Rouge2 Recall: 0.1633
- Rouge2 Fmeasure: 0.1786

## 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: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 50
- num_epochs: 3

### Training results

| Training Loss | Epoch | Step | Validation Loss | Rouge2 Precision | Rouge2 Recall | Rouge2 Fmeasure |
|:-------------:|:-----:|:----:|:---------------:|:----------------:|:-------------:|:---------------:|
| 5.8554        | 0.58  | 1500 | 3.2533          | 0.1              | 0.0744        | 0.0721          |
| 4.2403        | 1.16  | 3000 | 2.7020          | 0.1704           | 0.1174        | 0.1248          |
| 3.8091        | 1.74  | 4500 | 2.5844          | 0.2476           | 0.1617        | 0.1767          |
| 3.6589        | 2.32  | 6000 | 2.5289          | 0.2467           | 0.1621        | 0.1769          |
| 3.5802        | 2.9   | 7500 | 2.5082          | 0.2496           | 0.1633        | 0.1786          |


### Framework versions

- Transformers 4.39.3
- Pytorch 2.1.2
- Datasets 2.18.0
- Tokenizers 0.15.2