readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  metrics:
  - accuracy
  model-index:
  - name: flan-t5-large-intent-dailydialog_fs1.0-first
    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-intent-dailydialog_fs1.0-first
  
  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: 0.2463
  - Accuracy: 56.0758
  - Num: 7069
  - Gen Len: 4.4366
  
  ## 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: 2e-05
  - train_batch_size: 16
  - eval_batch_size: 48
  - seed: 1799
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: linear
  - num_epochs: 1
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Accuracy | Num  | Gen Len |
  |:-------------:|:-----:|:----:|:---------------:|:--------:|:----:|:-------:|
  | 0.6444        | 0.04  | 400  | 0.3113          | 46.6403  | 7069 | 4.7432  |
  | 0.2813        | 0.09  | 800  | 0.2797          | 50.87    | 7069 | 4.4159  |
  | 0.2623        | 0.13  | 1200 | 0.2676          | 53.5295  | 7069 | 4.4337  |
  | 0.2533        | 0.17  | 1600 | 0.2666          | 52.61    | 7069 | 4.4832  |
  | 0.246         | 0.22  | 2000 | 0.2717          | 53.4022  | 7069 | 4.5206  |
  | 0.2456        | 0.26  | 2400 | 0.2826          | 52.1997  | 7069 | 4.5299  |
  | 0.2434        | 0.3   | 2800 | 0.2541          | 55.3402  | 7069 | 4.4892  |
  | 0.235         | 0.35  | 3200 | 0.2486          | 56.5568  | 7069 | 4.4456  |
  | 0.2381        | 0.39  | 3600 | 0.2493          | 55.1422  | 7069 | 4.4289  |
  | 0.2283        | 0.43  | 4000 | 0.2478          | 56.0475  | 7069 | 4.3828  |
  | 0.2337        | 0.48  | 4400 | 0.2465          | 56.1041  | 7069 | 4.4261  |
  | 0.2277        | 0.52  | 4800 | 0.2575          | 54.8168  | 7069 | 4.5013  |
  | 0.2251        | 0.56  | 5200 | 0.2515          | 55.6231  | 7069 | 4.4892  |
  | 0.2235        | 0.61  | 5600 | 0.2613          | 54.449   | 7069 | 4.4756  |
  | 0.2249        | 0.65  | 6000 | 0.2463          | 56.0758  | 7069 | 4.4366  |
  | 0.2235        | 0.7   | 6400 | 0.2571          | 55.4251  | 7069 | 4.4736  |
  | 0.2238        | 0.74  | 6800 | 0.2537          | 55.5666  | 7069 | 4.4377  |
  | 0.2202        | 0.78  | 7200 | 0.2558          | 54.9583  | 7069 | 4.4855  |
  | 0.224         | 0.83  | 7600 | 0.2550          | 55.0856  | 7069 | 4.4603  |
  | 0.2186        | 0.87  | 8000 | 0.2506          | 56.0758  | 7069 | 4.4824  |
  
  
  ### Framework versions
  
  - Transformers 4.18.0
  - Pytorch 1.10.0+cu111
  - Datasets 2.5.1
  - Tokenizers 0.12.1
  