readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  datasets:
  - tweet_eval
  metrics:
  - accuracy
  model-index:
  - name: TweetEval_ELECTRA_5E
    results:
    - task:
        name: Text Classification
        type: text-classification
      dataset:
        name: tweet_eval
        type: tweet_eval
        config: sentiment
        split: train
        args: sentiment
      metrics:
      - name: Accuracy
        type: accuracy
        value: 0.9066666666666666
  ---
  
  <!-- 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. -->
  
  # TweetEval_ELECTRA_5E
  
  This model is a fine-tuned version of [google/electra-small-discriminator](https://huggingface.co/google/electra-small-discriminator) on the tweet_eval dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.2935
  - Accuracy: 0.9067
  
  ## 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: 1e-05
  - train_batch_size: 16
  - eval_batch_size: 8
  - seed: 42
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: linear
  - num_epochs: 5
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Accuracy |
  |:-------------:|:-----:|:----:|:---------------:|:--------:|
  | 0.6466        | 0.04  | 50   | 0.6006          | 0.7333   |
  | 0.5974        | 0.08  | 100  | 0.5769          | 0.7333   |
  | 0.5884        | 0.12  | 150  | 0.5486          | 0.7333   |
  | 0.5601        | 0.16  | 200  | 0.4799          | 0.76     |
  | 0.5125        | 0.2   | 250  | 0.4380          | 0.8533   |
  | 0.4603        | 0.24  | 300  | 0.4169          | 0.84     |
  | 0.4353        | 0.28  | 350  | 0.3775          | 0.86     |
  | 0.4498        | 0.32  | 400  | 0.3460          | 0.9      |
  | 0.4014        | 0.37  | 450  | 0.3812          | 0.8467   |
  | 0.4072        | 0.41  | 500  | 0.3383          | 0.88     |
  | 0.3891        | 0.45  | 550  | 0.3377          | 0.88     |
  | 0.3482        | 0.49  | 600  | 0.3289          | 0.8933   |
  | 0.3705        | 0.53  | 650  | 0.3162          | 0.8933   |
  | 0.3249        | 0.57  | 700  | 0.2967          | 0.9      |
  | 0.332         | 0.61  | 750  | 0.2925          | 0.8867   |
  | 0.3166        | 0.65  | 800  | 0.2916          | 0.9067   |
  | 0.334         | 0.69  | 850  | 0.3083          | 0.8667   |
  | 0.3039        | 0.73  | 900  | 0.2966          | 0.8867   |
  | 0.3066        | 0.77  | 950  | 0.3054          | 0.88     |
  | 0.3238        | 0.81  | 1000 | 0.3060          | 0.88     |
  | 0.308         | 0.85  | 1050 | 0.3103          | 0.88     |
  | 0.2889        | 0.89  | 1100 | 0.2922          | 0.88     |
  | 0.2773        | 0.93  | 1150 | 0.2986          | 0.8933   |
  | 0.3078        | 0.97  | 1200 | 0.2852          | 0.8933   |
  | 0.2529        | 1.01  | 1250 | 0.2957          | 0.8933   |
  | 0.2968        | 1.06  | 1300 | 0.2893          | 0.8867   |
  | 0.2536        | 1.1   | 1350 | 0.2902          | 0.88     |
  | 0.2836        | 1.14  | 1400 | 0.3085          | 0.88     |
  | 0.3066        | 1.18  | 1450 | 0.2909          | 0.88     |
  | 0.28          | 1.22  | 1500 | 0.2953          | 0.8867   |
  | 0.2549        | 1.26  | 1550 | 0.3019          | 0.8867   |
  | 0.2974        | 1.3   | 1600 | 0.2796          | 0.88     |
  | 0.2808        | 1.34  | 1650 | 0.2762          | 0.9      |
  | 0.2548        | 1.38  | 1700 | 0.2808          | 0.9      |
  | 0.2879        | 1.42  | 1750 | 0.2819          | 0.8933   |
  | 0.2583        | 1.46  | 1800 | 0.2904          | 0.88     |
  | 0.2387        | 1.5   | 1850 | 0.3016          | 0.8733   |
  | 0.2574        | 1.54  | 1900 | 0.2981          | 0.8933   |
  | 0.2589        | 1.58  | 1950 | 0.2907          | 0.8933   |
  | 0.2436        | 1.62  | 2000 | 0.2926          | 0.8867   |
  | 0.2606        | 1.66  | 2050 | 0.2807          | 0.8933   |
  | 0.2841        | 1.7   | 2100 | 0.2805          | 0.9      |
  | 0.2497        | 1.75  | 2150 | 0.2765          | 0.8867   |
  | 0.2866        | 1.79  | 2200 | 0.2821          | 0.9      |
  | 0.2614        | 1.83  | 2250 | 0.2759          | 0.8867   |
  | 0.2605        | 1.87  | 2300 | 0.2704          | 0.8933   |
  | 0.2365        | 1.91  | 2350 | 0.2623          | 0.9      |
  | 0.2274        | 1.95  | 2400 | 0.2651          | 0.8933   |
  | 0.2564        | 1.99  | 2450 | 0.2664          | 0.9      |
  | 0.2481        | 2.03  | 2500 | 0.2706          | 0.9      |
  | 0.2382        | 2.07  | 2550 | 0.2819          | 0.8933   |
  | 0.2351        | 2.11  | 2600 | 0.2848          | 0.9      |
  | 0.18          | 2.15  | 2650 | 0.2881          | 0.8933   |
  | 0.2343        | 2.19  | 2700 | 0.2983          | 0.9      |
  | 0.2043        | 2.23  | 2750 | 0.2908          | 0.8933   |
  | 0.2272        | 2.27  | 2800 | 0.3000          | 0.8867   |
  | 0.246         | 2.31