generated_from_trainer base_model:google/t5-v1_1-large license:apache-2.0 region:us
---
license: apache-2.0
base_model: google/t5-v1_1-large
tags:
- generated_from_trainer
model-index:
- name: ghc-google-t5-v1_1-large-intra_model-shuffle-human_annots_str
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# ghc-google-t5-v1_1-large-intra_model-shuffle-human_annots_str

This model is a fine-tuned version of [google/t5-v1_1-large](https://huggingface.co/google/t5-v1_1-large) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: nan

## 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: 0.0001
- 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: 200

### Training results

| Training Loss | Epoch | Step  | Validation Loss |
|:-------------:|:-----:|:-----:|:---------------:|
| 3.0844        | 1.0   | 689   | 3.0600          |
| 0.1027        | 2.0   | 1378  | 0.0872          |
| 0.1404        | 3.0   | 2067  | 0.0758          |
| 0.0846        | 4.0   | 2756  | 0.0725          |
| 0.079         | 5.0   | 3445  | 0.0707          |
| 0.0774        | 6.0   | 4134  | 0.0723          |
| 0.079         | 7.0   | 4823  | 0.0694          |
| 0.0677        | 8.0   | 5512  | 0.0709          |
| 0.0697        | 9.0   | 6201  | 0.0676          |
| 0.0715        | 10.0  | 6890  | 0.0711          |
| 0.0676        | 11.0  | 7579  | 0.0667          |
| 0.0776        | 12.0  | 8268  | 0.0659          |
| 0.0692        | 13.0  | 8957  | 0.0655          |
| 0.0621        | 14.0  | 9646  | 0.0659          |
| 0.0571        | 15.0  | 10335 | 0.0658          |
| 0.0724        | 16.0  | 11024 | 0.0658          |


### Framework versions

- Transformers 4.34.0
- Pytorch 2.1.0+cu121
- Datasets 2.6.1
- Tokenizers 0.14.1
