readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  metrics:
  - f1
  - precision
  - recall
  model-index:
  - name: flan-t5-large-dream-character
    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. -->
  
  # flan-t5-large-dream-character
  
  This model is a fine-tuned version of [google/flan-t5-large](https://huggingface.co/google/flan-t5-large) on the None dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.0937
  - Gen Len: 2.8625
  - F1: 0.6843
  - Precision: 0.7760
  - Recall: 0.6755
  
  ## 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: 0.0003
  - train_batch_size: 2
  - eval_batch_size: 2
  - seed: 42
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: cosine
  - lr_scheduler_warmup_ratio: 0.1
  - num_epochs: 5
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Gen Len | F1     | Precision | Recall |
  |:-------------:|:-----:|:----:|:---------------:|:-------:|:------:|:---------:|:------:|
  | 0.714         | 0.59  | 250  | 0.1678          | 3.025   | 0.2809 | 0.3302    | 0.3145 |
  | 0.1488        | 1.18  | 500  | 0.1332          | 2.1     | 0.4394 | 0.575     | 0.4082 |
  | 0.1206        | 1.78  | 750  | 0.1023          | 2.35    | 0.5491 | 0.6948    | 0.5205 |
  | 0.097         | 2.37  | 1000 | 0.0974          | 2.8375  | 0.5889 | 0.6956    | 0.5904 |
  | 0.0859        | 2.96  | 1250 | 0.0884          | 2.9     | 0.6610 | 0.7510    | 0.6574 |
  | 0.0635        | 3.55  | 1500 | 0.0926          | 2.4625  | 0.6429 | 0.7875    | 0.5930 |
  | 0.0581        | 4.15  | 1750 | 0.0930          | 2.75    | 0.6651 | 0.7754    | 0.6446 |
  | 0.0453        | 4.74  | 2000 | 0.0937          | 2.8625  | 0.6843 | 0.7760    | 0.6755 |
  
  
  ### Framework versions
  
  - Transformers 4.26.0
  - Pytorch 1.13.1+cu116
  - Datasets 2.9.0
  - Tokenizers 0.13.2
  