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--- |
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license: apache-2.0 |
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base_model: google/flan-t5-base |
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tags: |
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- generated_from_trainer |
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metrics: |
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- precision |
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- recall |
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- f1 |
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model-index: |
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- name: flan-t5-base-comma-correction |
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results: [] |
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--- |
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You |
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should probably proofread and complete it, then remove this comment. --> |
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# flan-t5-base-comma-correction |
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This model is a fine-tuned version of [google/flan-t5-base](https://huggingface.co/google/flan-t5-base) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.0492 |
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- Gen Len: 39.5298 |
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- Em Ic: 0.9334 |
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- Em: 0.6384 |
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- Precision: 0.9141 |
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- Recall: 0.8575 |
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- F1: 0.8248 |
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- Levinstein Ratio: 0.9955 |
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## Model description |
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More information needed |
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## Intended uses & limitations |
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More information needed |
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## Training and evaluation data |
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More information needed |
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## Training procedure |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- learning_rate: 2e-05 |
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- train_batch_size: 64 |
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- eval_batch_size: 64 |
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- seed: 42 |
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: cosine |
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- lr_scheduler_warmup_steps: 200 |
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- num_epochs: 3.0 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Gen Len | Em Ic | Em | Precision | Recall | F1 | Levinstein Ratio | |
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|:-------------:|:-----:|:----:|:---------------:|:-------:|:------:|:------:|:---------:|:------:|:------:|:----------------:| |
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| 0.042 | 1.0 | 2159 | 0.0500 | 39.4971 | 0.9328 | 0.6256 | 0.9175 | 0.8452 | 0.8165 | 0.9954 | |
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| 0.0342 | 2.0 | 4318 | 0.0492 | 39.5158 | 0.9334 | 0.6361 | 0.9159 | 0.8546 | 0.8229 | 0.9955 | |
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| 0.0346 | 3.0 | 6477 | 0.0492 | 39.5298 | 0.9334 | 0.6384 | 0.9141 | 0.8575 | 0.8248 | 0.9955 | |
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### Framework versions |
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- Transformers 4.35.0 |
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- Pytorch 2.1.0+cu118 |
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- Datasets 2.14.6 |
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- Tokenizers 0.14.1 |
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