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Add evaluation results on the default config and train split of aslg_pc12
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metadata
language:
  - en
license: apache-2.0
tags:
  - generated_from_trainer
datasets:
  - aslg_pc12
metrics:
  - bertscore
  - bleu
  - sacrebleu
  - comet
base_model: t5-small
pipeline_tag: translation
model-index:
  - name: t5_small_gloss_to_text_random_0.1
    results:
      - task:
          type: translation
          name: Translation
        dataset:
          name: aslg_pc12
          type: aslg_pc12
          config: default
          split: train
        metrics:
          - type: bleu
            value: 68.0647
            name: BLEU
            verified: true
            verifyToken: >-
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          - type: loss
            value: 0.3523485064506531
            name: loss
            verified: true
            verifyToken: >-
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          - type: gen_len
            value: 15.6202
            name: gen_len
            verified: true
            verifyToken: >-
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t5_small_gloss_to_text_random_0.1

This model is a fine-tuned version of t5-small on an unknown dataset.

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: 5e-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
  • num_epochs: 3.0

Training results

Framework versions

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