readme: ---
  tags:
  - generated_from_trainer
  model-index:
  - name: bert-tiny-finetuned-legal-definitions-longer-downstream-alt
    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. -->
  
  # bert-tiny-finetuned-legal-definitions-longer-downstream-alt
  
  This model is a fine-tuned version of [muhtasham/bert-tiny-finetuned-legal-definitions-longer](https://huggingface.co/muhtasham/bert-tiny-finetuned-legal-definitions-longer) on the None dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.2301
  - Micro f1: 0.0
  - Macro f1: 0.0
  
  ## 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: 4096
  - eval_batch_size: 1024
  - seed: 42
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: linear
  - num_epochs: 1000
  
  ### Training results
  
  | Training Loss | Epoch  | Step | Validation Loss | Micro f1 | Macro f1 |
  |:-------------:|:------:|:----:|:---------------:|:--------:|:--------:|
  | 0.6908        | 1.0    | 3    | 0.6878          | 0.1142   | 0.0900   |
  | 0.6871        | 2.0    | 6    | 0.6838          | 0.1152   | 0.0834   |
  | 0.6833        | 3.0    | 9    | 0.6799          | 0.1161   | 0.0763   |
  | 0.6799        | 4.0    | 12   | 0.6759          | 0.1150   | 0.0697   |
  | 0.6761        | 5.0    | 15   | 0.6720          | 0.1135   | 0.0617   |
  | 0.6723        | 6.0    | 18   | 0.6681          | 0.1100   | 0.0513   |
  | 0.6688        | 7.0    | 21   | 0.6642          | 0.1069   | 0.0442   |
  | 0.6652        | 8.0    | 24   | 0.6604          | 0.1019   | 0.0379   |
  | 0.6617        | 9.0    | 27   | 0.6566          | 0.0940   | 0.0296   |
  | 0.658         | 10.0   | 30   | 0.6528          | 0.0835   | 0.0252   |
  | 0.6544        | 11.0   | 33   | 0.6491          | 0.0696   | 0.0218   |
  | 0.6511        | 12.0   | 36   | 0.6455          | 0.0463   | 0.0169   |
  | 0.6475        | 13.0   | 39   | 0.6418          | 0.0287   | 0.0131   |
  | 0.6441        | 14.0   | 42   | 0.6383          | 0.0133   | 0.0085   |
  | 0.6407        | 15.0   | 45   | 0.6348          | 0.0044   | 0.0031   |
  | 0.6375        | 16.0   | 48   | 0.6313          | 0.0012   | 0.0010   |
  | 0.634         | 17.0   | 51   | 0.6279          | 0.0004   | 0.0003   |
  | 0.6308        | 18.0   | 54   | 0.6246          | 0.0      | 0.0      |
  | 0.6276        | 19.0   | 57   | 0.6213          | 0.0      | 0.0      |
  | 0.6244        | 20.0   | 60   | 0.6180          | 0.0      | 0.0      |
  | 0.6212        | 21.0   | 63   | 0.6147          | 0.0      | 0.0      |
  | 0.6179        | 22.0   | 66   | 0.6115          | 0.0      | 0.0      |
  | 0.6148        | 23.0   | 69   | 0.6083          | 0.0      | 0.0      |
  | 0.6116        | 24.0   | 72   | 0.6051          | 0.0      | 0.0      |
  | 0.6085        | 25.0   | 75   | 0.6019          | 0.0      | 0.0      |
  | 0.6055        | 26.0   | 78   | 0.5987          | 0.0      | 0.0      |
  | 0.6024        | 27.0   | 81   | 0.5955          | 0.0      | 0.0      |
  | 0.5992        | 28.0   | 84   | 0.5923          | 0.0      | 0.0      |
  | 0.5961        | 29.0   | 87   | 0.5891          | 0.0      | 0.0      |
  | 0.593         | 30.0   | 90   | 0.5859          | 0.0      | 0.0      |
  | 0.5898        | 31.0   | 93   | 0.5828          | 0.0      | 0.0      |
  | 0.5866        | 32.0   | 96   | 0.5796          | 0.0      | 0.0      |
  | 0.5835        | 33.0   | 99   | 0.5764          | 0.0      | 0.0      |
  | 0.5805        | 34.0   | 102  | 0.5732          | 0.0      | 0.0      |
  | 0.5775        | 35.0   | 105  | 0.5700          | 0.0      | 0.0      |
  | 0.5739        | 36.0   | 108  | 0.5668          | 0.0      | 0.0      |
  | 0.5709        | 37.0   | 111  | 0.5636          | 0.0      | 0.0      |
  | 0.5677        | 38.0   | 114  | 0.5604          | 0.0      | 0.0      |
  | 0.5647        | 39.0   | 117  | 0.5572          | 0.0      | 0.0      |
  | 0.5614        | 40.0   | 120  | 0.5540          | 0.0      | 0.0      |
  | 0.5582        | 41.0   | 123  | 0.5508          | 0.0      | 0.0      |
  | 0.5549        | 42.0   | 126  | 0.5476          | 0.0      | 0.0      |
  | 0.552         | 43.0   | 129  | 0.5444          | 0.0      | 0.0      |
  | 0.5486        | 44.0   | 132  | 0.5412          | 0.0      | 0.0      |
  | 0.5458        | 45.0   | 135  | 0.5381          | 0.0      | 0.0      |
  | 0.5426        | 46.0   | 138  | 0.5349          | 0.0      | 0.0      |
  | 0.539         | 47.0   | 141  | 0.5317          | 0.0      | 0.0      |
  | 0.5359        | 48.0   | 144  | 0.5285          | 0.0      | 0.0      |
  | 0.5327        | 49.0   | 147  | 0.5254          | 0.0      | 0.0      |
  | 0.5295        | 50.0   | 150  | 0.5222          | 0.0 