---
license: apache-2.0
base_model: google/t5-v1_1-small
tags:
- generated_from_trainer
model-index:
- name: SChem5Labels-google-t5-v1_1-small-intra_model
  results: []
---

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# SChem5Labels-google-t5-v1_1-small-intra_model

This model is a fine-tuned version of [google/t5-v1_1-small](https://huggingface.co/google/t5-v1_1-small) on the None dataset.
It achieves the following results on the evaluation set:
- Train Loss: 0.7917
- Loss: inf
- Losses: [1, 1, 0.4, 0.4, 1.0, 1, 1.0, 1.0, 0.4, 0.8, 1.0, 0.6000000000000001, 0.4, 1, 0.8, 1.0, 1, 0.4, 1, 1.0, 1, 1.0, 1.0, 1.0, 1.0, 1.0, 1, 1.0, 1, 0.8, 0.2, 0.8, 0.6000000000000001, 0.6000000000000001, 1, 1.0, 1, 0.8, 1.0, 1, 1.0, 1.0, 0.4, 1, 1, 1.0, 0.8, 1, 1.0, 0.6000000000000001, 1.0, 1.0, 1.0, 1, 1.0, 1, 1.0, 0.6000000000000001, 1, 1.0, 1, 1, 1, 0.4, 1, 1, 0.6000000000000001, 0.6000000000000001, 0.6000000000000001, 0.6000000000000001, 0.6000000000000001, 1, 1.0, 0.8, 0.6000000000000001, 0.6000000000000001, 1, 0.6000000000000001, 1.0, 0.6000000000000001, 1.0, 0.6000000000000001, 1.0, 0.6000000000000001, 1.0, 0.6000000000000001, 0.6000000000000001, 0.6000000000000001, 0.6000000000000001, 0.0, 0.6000000000000001, 0.6000000000000001, 0.2, 0.6000000000000001, 0.6000000000000001, 0.6000000000000001, 0.6000000000000001, 1.0, 0.8, 0.6000000000000001, 0.6000000000000001, 1.0, 0.6000000000000001, 0.6000000000000001, 1, 0.6000000000000001, 0.6000000000000001, 0.6000000000000001, 1.0, 1.0, 0.6000000000000001, 0.0, 0.6000000000000001, 0.0, 0.6000000000000001, 0.6000000000000001, 0.6000000000000001, 0.6000000000000001, 1, 1, 1.0, 0.6000000000000001, 1.0, 0.6000000000000001, 0.6000000000000001, 0.8, 1.0, 0.6000000000000001, 0.6000000000000001, 1.0, 1.0, 0.6000000000000001, 1.0, 1.0, 1.0, 1.0, 1, 0.6000000000000001, 0.6000000000000001, 0.6000000000000001, 0.6000000000000001, 1.0, 0.6000000000000001, 0.6000000000000001, 0.6000000000000001, 0.6000000000000001, 1.0, 0.2, 1.0, 0.6000000000000001, 1.0, 1, 1.0, 0.6000000000000001, 0.6000000000000001, 1, 1.0, 0.6000000000000001, 1.0, 0.6000000000000001, 0.4, 1.0, 1, 1.0, 1.0, 0.6000000000000001, 0.6000000000000001, 1.0, 0.6000000000000001, 0.6000000000000001, 0.6000000000000001, 0.6000000000000001, 1, 0.6000000000000001, 0.8, 0.6000000000000001, 1, 1.0, 1.0, 1.0, 0.6000000000000001, 1, 1.0, 0.8, 0.8, 0.6000000000000001, 0.8, 1.0, 0.4, 1.0, 0.6000000000000001, 1.0, 0.8, 1.0, 0.6000000000000001, 0.6000000000000001, 0.4, 0.6000000000000001, 0.6000000000000001, 1.0, 0.6000000000000001, 1.0, 1, 1.0, 1, 1, 0.6000000000000001, 1.0, 1.0, 0.8, 1, 0.6000000000000001, 0.6000000000000001, 1, 1, 1.0, 1, 0.8, 0.6000000000000001, 0.4, 1, 1.0, 0.6000000000000001, 1, 1, 1.0, 1, 1, 0.4, 1, 1.0, 1, 0.0, 0.8, 0.6000000000000001, 0.4, 1.0, 0.2, 1.0, 0.6000000000000001, 0.2, 0.4, 1, 0.6000000000000001, 1.0, 1, 1.0, 1, 1, 0.6000000000000001, 1, 1, 1, 0.0, 1.0, 0.6000000000000001, 0.6000000000000001, 1.0, 1, 0.6000000000000001, 0.6000000000000001, 0.4, 0.6000000000000001, 1, 1.0, 1, 1, 0.4, 1.0, 1.0, 1, 0.8, 1, 0.6000000000000001, 1.0, 0.6000000000000001, 0.6000000000000001, 0.6000000000000001, 0.6000000000000001, 1, 1.0, 0.2, 1.0, 1, 0.8, 1, 1, 0.4, 0.4, 1.0, 0.0, 1.0, 0.8, 0.6000000000000001, 1.0, 1.0, 1.0, 0.8, 1.0, 0.6000000000000001, 0.6000000000000001, 0.6000000000000001, 1.0, 1.0, 0.6000000000000001, 1.0, 1.0, 1.0, 1.0, 1.0, 0.8, 1.0, 1, 1.0, 1, 1.0, 0.6000000000000001, 0.4, 1, 0.6000000000000001, 0.4, 1, 1, 1, 1.0, 0.4, 1, 0.6000000000000001, 0.6000000000000001, 0.6000000000000001, 0.6000000000000001, 1.0, 0.6000000000000001, 1, 0.6000000000000001, 1.0, 0.6000000000000001, 0.8, 1, 1.0, 0.4, 1.0, 0.8, 1, 1.0, 0.8, 0.4, 1.0, 0.4, 0.6000000000000001, 1, 0.6000000000000001, 1.0, 1, 0.6000000000000001, 1.0, 0.6000000000000001, 0.6000000000000001, 1, 1]

## 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 | Train Loss | Validation Loss | Losses                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                       |
|:-------------:|:-----:|:----:|:----------:|:---------------:|:--------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------:|
| 405015552.0   | 1.0   | 99   | 0.7933     | 389655456.0     | [1.0, 0.6000000000000001, 1.0, 1, 0.6000000000000001, 0.0, 0.6000000000000001, 0.6000000000000001, 0.4, 0.8, 0.8, 1, 1, 1, 0.4, 0.4, 1.0, 1, 0.6000000000000001, 1, 1, 1.0, 1.0, 0.8, 0.4, 1, 0.6000000000000001, 0.8, 0.6000000000000001, 1.0, 1.0, 1, 0.6000000000000001, 1.0, 1, 0.8, 1.0, 1.0, 0.6000000000000001, 0.6000000000000001, 0.6000000000000001, 0.4, 1, 1, 1.0, 0.8, 1, 1.0, 1, 1.0, 1.0, 1.0, 1.0, 0.6000000000000001, 1.0, 1.0, 1, 1.0, 1.0, 1.0, 0.8, 1.0, 0.6000000000000001, 0.6000000000000001, 1.0, 1, 1, 1.0, 0.6000000000000001, 1, 0.6000000000000001, 0.4, 1.0, 1.0, 1.0, 0.6000000000000001, 1.0, 0.6000000000000001, 0.8, 1.0, 1.0, 1.0, 1.0, 1.0, 1, 0.6000000000000001, 1, 1.0, 0.6000000000000001, 1.0, 0.6000000000000001, 0.6000000000000001, 1.0, 0.6000000000000001, 0.8, 1, 0.6000000000000001, 0.4, 1.0, 0.6000000000000001, 0.6000000000000001, 1, 1, 0.6000000000000001, 1, 1.0, 1, 0.4, 1, 0.8, 0.6000000000000001, 1, 1.0, 1.0, 0.6000000000000001, 1, 1, 1.0, 1, 0.0, 0.4, 1, 0.6000000000000001, 0.4, 0.6000000000000001, 0.6000000000000001, 0.6000000000000001, 0.8, 0.6000000000000001, 0.6000000000000001, 0.4, 0.6000000000000001, 1, 0.6000000000000001, 0.6000000000000001, 1, 1.0, 0.8, 0.6000000000000001, 0.6000000000000001, 1.0, 1, 0.6000000000000001, 0.6000000000000001, 0.8, 0.6000000000000001, 1.0, 1.0, 1, 0.6000000000000001, 1, 0.8, 0.6000000000000001, 0.6000000000000001, 0.6000000000000001, 1, 1, 1.0, 0.8, 1.0, 0.6000000000000001, 0.6000000000000001, 1, 0.2, 0.8, 0.6000000000000001, 0.6000000000000001, 0.6000000000000001, 0.8, 1, 1, 0.8, 0.6000000000000001, 0.4, 0.6000000000000001, 0.4, 1.0, 1.0, 0.6000000000000001, 0.8, 0.4, 0.6000000000000001, 0.6000000000000001, 0.6000000000000001, 1.0, 1, 0.6000000000000001, 0.6000000000000001, 1.0, 0.6000000000000001, 0.8, 1, 1.0, 1.0, 1, 1.0, 1.0, 1.0, 1, 0.6000000000000001, 1, 1.0, 1.0, 1.0, 1.0, 1.0, 0.6000000000000001, 1, 1, 0.8, 1.0, 1.0, 0.6000000000000001, 0.8, 0.0, 1.0, 1.0, 0.6000000000000001, 1.0, 0.6000000000000001, 1, 1.0, 1, 0.6000000000000001, 0.6000000000000001, 1, 1, 0.6000000000000001, 1, 0.8, 1.0, 1.0, 0.6000000000000001, 0.6000000000000001, 1.0, 0.4, 1, 1, 0.6000000000000001, 0.6000000000000001, 0.8, 1, 1.0, 1, 0.6000000000000001, 1.0, 0.8, 0.8, 0.6000000000000001, 1, 1, 0.6000000000000001, 1.0, 1, 0.6000000000000001, 0.8, 0.6000000000000001, 1, 0.6000000000000001, 0.0, 1, 0.6000000000000001, 1.0, 1, 0.0, 0.6000000000000001, 0.6000000000000001, 0.6000000000000001, 1.0, 0.6000000000000001, 0.6000000000000001, 0.4, 1, 1, 1, 1.0, 0.4, 1, 1.0, 0.0, 0.6000000000000001, 1, 1, 0.8, 0.6000000000000001, 0.4, 0.4, 1, 0.4, 1.0, 1.0, 0.6000000000000001, 0.6000000000000001, 1.0, 0.8, 1, 1.0, 1, 0.6000000000000001, 0.8, 1, 0.6000000000000001, 0.6000000000000001, 0.4, 1, 0.6000000000000001, 0.6000000000000001, 1.0, 1, 0.8, 0.4, 1, 1, 0.4, 0.6000000000000001, 1.0, 1, 1.0, 0.6000000000000001, 0.6000000000000001, 1.0, 1.0, 0.6000000000000001, 1, 1.0, 0.8, 0.8, 1.0, 0.6000000000000001, 0.6000000000000001, 0.6000000000000001, 0.6000000000000001, 0.8, 1, 0.6000000000000001, 0.6000000000000001, 0.6000000000000001, 0.4, 0.6000000000000001, 0.6000000000000001, 1, 0.4, 1, 1, 1, 0.6000000000000001, 0.8, 1, 1.0, 1.0, 0.2, 1.0, 1.0, 1, 0.6000000000000001, 1.0, 0.4, 0.6000000000000001, 1]                                                                                                                                                                                      |
| 414025753.6   | 2.0   | 198  | 0.7944     | 389655456.0     | [1.0, 0.6000000000000001, 1.0, 1, 0.6000000000000001, 0.0, 0.6000000000000001, 0.6000000000000001, 0.4, 1.0, 0.8, 1, 1, 0.6000000000000001, 0.4, 0.4, 1.0, 1, 1, 1.0, 1, 1.0, 1.0, 0.6000000000000001, 0.4, 0.6000000000000001, 0.6000000000000001, 0.8, 0.6000000000000001, 1.0, 1.0, 0.6000000000000001, 0.6000000000000001, 1.0, 0.8, 0.8, 1.0, 1.0, 0.6000000000000001, 0.6000000000000001, 0.6000000000000001, 1.0, 0.8, 1, 1.0, 0.8, 1, 1.0, 0.6000000000000001, 1.0, 1.0, 1.0, 1.0, 0.6000000000000001, 1.0, 1.0, 1, 1.0, 1.0, 1.0, 1, 1.0, 0.6000000000000001, 0.6000000000000001, 1.0, 0.8, 1, 1.0, 0.6000000000000001, 1, 0.6000000000000001, 0.4, 1.0, 1.0, 1.0, 0.6000000000000001, 0.6000000000000001, 0.6000000000000001, 0.8, 1.0, 1.0, 1.0, 1.0, 1.0, 1, 0.6000000000000001, 1, 1.0, 0.6000000000000001, 1.0, 0.6000000000000001, 0.6000000000000001, 1.0, 0.6000000000000001, 1.0, 1, 0.6000000000000001, 0.4, 1.0, 0.6000000000000001, 0.6000000000000001, 1, 1, 0.6000000000000001, 0.6000000000000001, 1.0, 1, 0.4, 0.8, 0.6000000000000001, 0.6000000000000001, 1, 0.6000000000000001, 1.0, 0.6000000000000001, 1, 1, 1.0, 0.6000000000000001, 0.0, 1.0, 1, 1, 0.4, 0.6000000000000001, 0.6000000000000001, 0.6000000000000001, 0.8, 0.6000000000000001, 0.6000000000000001, 0.4, 0.6000000000000001, 1, 0.6000000000000001, 0.6000000000000001, 1, 0.6000000000000001, 0.8, 1.0, 0.6000000000000001, 1.0, 1, 0.6000000000000001, 0.6000000000000001, 0.8, 0.6000000000000001, 1.0, 1.0, 1, 1, 1, 0.8, 0.6000000000000001, 0.6000000000000001, 0.6000000000000001, 1.0, 1, 1.0, 0.0, 1.0, 0.6000000000000001, 0.6000000000000001, 1, 0.8, 1.0, 0.6000000000000001, 0.6000000000000001, 1.0, 0.8, 1, 1, 1, 0.6000000000000001, 0.4, 0.6000000000000001, 0.4, 1.0, 1.0, 0.6000000000000001, 0.8, 0.4, 0.6000000000000001, 0.6000000000000001, 0.6000000000000001, 1.0, 1, 0.6000000000000001, 0.4, 1.0, 0.6000000000000001, 1, 1, 1.0, 1.0, 1, 1.0, 1.0, 1.0, 1, 0.6000000000000001, 1, 1.0, 1.0, 1.0, 1.0, 1.0, 0.6000000000000001, 1, 1, 1.0, 1.0, 1.0, 0.6000000000000001, 1, 0.0, 0.6000000000000001, 0.6000000000000001, 0.6000000000000001, 1.0, 0.6000000000000001, 1, 1.0, 1, 0.6000000000000001, 0.6000000000000001, 1, 1, 0.6000000000000001, 1, 0.8, 0.6000000000000001, 1.0, 0.6000000000000001, 0.6000000000000001, 1.0, 0.4, 1, 1, 0.6000000000000001, 0.6000000000000001, 0.8, 1, 1.0, 1, 0.6000000000000001, 1.0, 0.8, 0.8, 0.6000000000000001, 1, 1, 0.6000000000000001, 0.6000000000000001, 1, 0.6000000000000001, 1.0, 1.0, 0.8, 0.6000000000000001, 0.0, 0.6000000000000001, 0.6000000000000001, 1.0, 0.8, 0.4, 0.6000000000000001, 0.6000000000000001, 0.6000000000000001, 1.0, 0.6000000000000001, 0.6000000000000001, 0.4, 1, 1, 1, 1.0, 0.4, 1, 0.6000000000000001, 0.4, 0.6000000000000001, 0.6000000000000001, 1, 1, 0.6000000000000001, 0.4, 1, 1, 0.4, 1.0, 1.0, 0.6000000000000001, 1.0, 1.0, 0.8, 1.0, 1.0, 0.6000000000000001, 0.6000000000000001, 0.8, 1, 0.6000000000000001, 0.6000000000000001, 0.4, 1, 1.0, 0.6000000000000001, 1.0, 1, 1.0, 0.4, 1, 1, 0.4, 0.6000000000000001, 1.0, 1, 1.0, 0.6000000000000001, 1.0, 1.0, 1.0, 0.6000000000000001, 1, 1, 1, 1, 1.0, 0.6000000000000001, 1.0, 0.6000000000000001, 0.6000000000000001, 0.8, 1, 0.6000000000000001, 0.6000000000000001, 0.6000000000000001, 1.0, 0.6000000000000001, 0.6000000000000001, 0.6000000000000001, 0.4, 1, 1, 0.6000000000000001, 0.6000000000000001, 0.8, 1, 0.6000000000000001, 1.0, 0.8, 1.0, 1.0, 1, 0.6000000000000001, 1.0, 0.4, 0.6000000000000001, 1] |
| 408233881.6   | 3.0   | 297  | 0.7944     | 389655424.0     | [1.0, 0.6000000000000001, 1.0, 1, 0.6000000000000001, 0.0, 0.6000000000000001, 0.6000000000000001, 0.4, 1.0, 0.8, 1, 1, 0.6000000000000001, 0.4, 0.4, 1.0, 1, 1, 1.0, 1, 1.0, 1.0, 0.6000000000000001, 0.4, 0.6000000000000001, 0.6000000000000001, 0.8, 0.6000000000000001, 1.0, 1.0, 0.6000000000000001, 0.6000000000000001, 1.0, 0.8, 0.8, 1.0, 1.0, 0.6000000000000001, 0.6000000000000001, 0.6000000000000001, 1.0, 0.8, 1, 1.0, 0.8, 1, 1.0, 0.6000000000000001, 1.0, 1.0, 1.0, 1.0, 0.6000000000000001, 1.0, 1.0, 1, 1.0, 1.0, 1.0, 1, 1.0, 0.6000000000000001, 0.6000000000000001, 1.0, 0.8, 1, 1.0, 0.6000000000000001, 1, 0.6000000000000001, 0.4, 1.0, 1.0, 1.0, 0.6000000000000001, 0.6000000000000001, 0.6000000000000001, 0.8, 1.0, 1.0, 1.0, 1.0, 1.0, 1, 0.6000000000000001, 1, 1.0, 0.6000000000000001, 1.0, 0.6000000000000001, 0.6000000000000001, 1.0, 0.6000000000000001, 1.0, 1, 0.6000000000000001, 0.4, 1.0, 0.6000000000000001, 0.6000000000000001, 1, 1, 0.6000000000000001, 0.6000000000000001, 1.0, 1, 0.4, 0.8, 0.6000000000000001, 0.6000000000000001, 1, 0.6000000000000001, 1.0, 0.6000000000000001, 1, 1, 1.0, 0.6000000000000001, 0.0, 1.0, 1, 1, 0.4, 0.6000000000000001, 0.6000000000000001, 0.6000000000000001, 0.8, 0.6000000000000001, 0.6000000000000001, 0.4, 0.6000000000000001, 1, 0.6000000000000001, 0.6000000000000001, 1, 0.6000000000000001, 0.8, 1.0, 0.6000000000000001, 1.0, 1, 0.6000000000000001, 0.6000000000000001, 0.8, 0.6000000000000001, 1.0, 1.0, 1, 1, 1, 0.8, 0.6000000000000001, 0.6000000000000001, 0.6000000000000001, 1.0, 1, 1.0, 0.0, 1.0, 0.6000000000000001, 0.6000000000000001, 1, 0.8, 1.0, 0.6000000000000001, 0.6000000000000001, 1.0, 0.8, 1, 1, 1, 0.6000000000000001, 0.4, 0.6000000000000001, 0.4, 1.0, 1.0, 0.6000000000000001, 0.8, 0.4, 0.6000000000000001, 0.6000000000000001, 0.6000000000000001, 1.0, 1, 0.6000000000000001, 0.4, 1.0, 0.6000000000000001, 1, 1, 1.0, 1.0, 1, 1.0, 1.0, 1.0, 1, 0.6000000000000001, 1, 1.0, 1.0, 1.0, 1.0, 1.0, 0.6000000000000001, 1, 1, 1.0, 1.0, 1.0, 0.6000000000000001, 1, 0.0, 0.6000000000000001, 0.6000000000000001, 0.6000000000000001, 1.0, 0.6000000000000001, 1, 1.0, 1, 0.6000000000000001, 0.6000000000000001, 1, 1, 0.6000000000000001, 1, 0.8, 0.6000000000000001, 1.0, 0.6000000000000001, 0.6000000000000001, 1.0, 0.4, 1, 1, 0.6000000000000001, 0.6000000000000001, 0.8, 1, 1.0, 1, 0.6000000000000001, 1.0, 0.8, 0.8, 0.6000000000000001, 1, 1, 0.6000000000000001, 0.6000000000000001, 1, 0.6000000000000001, 1.0, 1.0, 0.8, 0.6000000000000001, 0.0, 0.6000000000000001, 0.6000000000000001, 1.0, 0.8, 0.4, 0.6000000000000001, 0.6000000000000001, 0.6000000000000001, 1.0, 0.6000000000000001, 0.6000000000000001, 0.4, 1, 1, 1, 1.0, 0.4, 1, 0.6000000000000001, 0.4, 0.6000000000000001, 0.6000000000000001, 1, 1, 0.6000000000000001, 0.4, 1, 1, 0.4, 1.0, 1.0, 0.6000000000000001, 1.0, 1.0, 0.8, 1.0, 1.0, 0.6000000000000001, 0.6000000000000001, 0.8, 1, 0.6000000000000001, 0.6000000000000001, 0.4, 1, 1.0, 0.6000000000000001, 1.0, 1, 1.0, 0.4, 1, 1, 0.4, 0.6000000000000001, 1.0, 1, 1.0, 0.6000000000000001, 1.0, 1.0, 1.0, 0.6000000000000001, 1, 1, 1, 1, 1.0, 0.6000000000000001, 1.0, 0.6000000000000001, 0.6000000000000001, 0.8, 1, 0.6000000000000001, 0.6000000000000001, 0.6000000000000001, 1.0, 0.6000000000000001, 0.6000000000000001, 0.6000000000000001, 0.4, 1, 1, 0.6000000000000001, 0.6000000000000001, 0.8, 1, 0.6000000000000001, 1.0, 0.8, 1.0, 1.0, 1, 0.6000000000000001, 1.0, 0.4, 0.6000000000000001, 1] |
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### Framework versions

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