---
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-dataset-frequency-model_annots_str
  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. -->

# ghc-google-t5-v1_1-large-intra_model-dataset-frequency-model_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: 32
- eval_batch_size: 32
- 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 |
|:-------------:|:-----:|:-----:|:---------------:|
| 6.1892        | 1.0   | 345   | 6.6229          |
| 5.2951        | 2.0   | 690   | 5.5307          |
| 0.2702        | 3.0   | 1035  | 0.2511          |
| 0.2605        | 4.0   | 1380  | 0.2295          |
| 0.2635        | 5.0   | 1725  | 0.2378          |
| 0.2405        | 6.0   | 2070  | 0.2250          |
| 0.2605        | 7.0   | 2415  | 0.2226          |
| 0.2235        | 8.0   | 2760  | 0.2237          |
| 0.2303        | 9.0   | 3105  | 0.2199          |
| 0.2378        | 10.0  | 3450  | 0.2214          |
| 0.24          | 11.0  | 3795  | 0.2169          |
| 0.2236        | 12.0  | 4140  | 0.2183          |
| 0.2079        | 13.0  | 4485  | 0.2184          |
| 0.2594        | 14.0  | 4830  | 0.2159          |
| 0.2303        | 15.0  | 5175  | 0.2170          |
| 0.2238        | 16.0  | 5520  | 0.2146          |
| 0.2071        | 17.0  | 5865  | 0.2161          |
| 0.2129        | 18.0  | 6210  | 0.2130          |
| 0.2297        | 19.0  | 6555  | 0.2133          |
| 0.2434        | 20.0  | 6900  | 0.2158          |
| 0.2158        | 21.0  | 7245  | 0.2147          |
| 0.2222        | 22.0  | 7590  | 0.2166          |
| 0.2388        | 23.0  | 7935  | 0.2127          |
| 0.2132        | 24.0  | 8280  | 0.2123          |
| 0.2269        | 25.0  | 8625  | 0.2136          |
| 0.2237        | 26.0  | 8970  | 0.2142          |
| 0.2064        | 27.0  | 9315  | 0.2135          |
| 0.2329        | 28.0  | 9660  | 0.2140          |
| 0.2319        | 29.0  | 10005 | 0.2140          |


### Framework versions

- Transformers 4.34.0
- Pytorch 2.1.0+cu121
- Datasets 2.14.5
- Tokenizers 0.14.1