transformers pytorch electra text-classification generated_from_trainer dataset:tweet_eval license:apache-2.0 model-index autotrain_compatible endpoints_compatible region:us
---
datasets:
- tweet_eval
license: apache-2.0
metrics:
- accuracy
tags:
- generated_from_trainer
model-index:
- name: TweetEval_ELECTRA_5E
  results:
  - task:
      type: text-classification
      name: Text Classification
    dataset:
      name: tweet_eval
      type: tweet_eval
      config: sentiment
      split: train
      args: sentiment
    metrics:
    - type: accuracy
      value: 0.9066666666666666
      name: Accuracy
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# 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  | 2850 | 0.3136          | 0.8867   |
| 0.2577        | 2.35  | 2900 | 0.3126          | 0.88     |
| 0.2316        | 2.39  | 2950 | 0.2803          | 0.8933   |
| 0.2156        | 2.44  | 3000 | 0.2737          | 0.9067   |
| 0.223         | 2.48  | 3050 | 0.2883          | 0.8933   |
| 0.2215        | 2.52  | 3100 | 0.2660          | 0.8867   |
| 0.2488        | 2.56  | 3150 | 0.2551          | 0.9      |
| 0.2095        | 2.6   | 3200 | 0.2645          | 0.9      |
| 0.2247        | 2.64  | 3250 | 0.2751          | 0.8933   |
| 0.2292        | 2.68  | 3300 | 0.2851          | 0.8867   |
| 0.237         | 2.72  | 3350 | 0.2824          | 0.8867   |
| 0.2086        | 2.76  | 3400 | 0.2805          | 0.8867   |
| 0.2063        | 2.8   | 3450 | 0.2771          | 0.9      |
| 0.2015        | 2.84  | 3500 | 0.2981          | 0.8933   |
| 0.2036        | 2.88  | 3550 | 0.2937          | 0.8933   |
| 0.247         | 2.92  | 3600 | 0.2985          | 0.8933   |
| 0.23          | 2.96  | 3650 | 0.2866          | 0.9067   |
| 0.2625        | 3.0   | 3700 | 0.2836          | 0.9      |
| 0.2064        | 3.04  | 3750 | 0.2911          | 0.8933   |
| 0.1867        | 3.08  | 3800 | 0.2868          | 0.8933   |
| 0.2143        | 3.12  | 3850 | 0.2903          | 0.9      |
| 0.1993        | 3.17  | 3900 | 0.2987          | 0.8933   |
| 0.1762        | 3.21  | 3950 | 0.3066          | 0.9067   |
| 0.1935        | 3.25  | 4000 | 0.3185          | 0.8867   |
| 0.234         | 3.29  | 4050 | 0.3043          | 0.9067   |
| 0.195         | 3.33  | 4100 | 0.2905          | 0.9067   |
| 0.2434        | 3.37  | 4150 | 0.3081          | 0.9      |
| 0.2168        | 3.41  | 4200 | 0.2919          | 0.9067   |
| 0.2044        | 3.45  | 4250 | 0.2903          | 0.9      |
| 0.2419        | 3.49  | 4300 | 0.2955          | 0.8933   |
| 0.191         | 3.53  | 4350 | 0.2957          | 0.9067   |
| 0.1927        | 3.57  | 4400 | 0.3075          | 0.8933   |
| 0.2267        | 3.61  | 4450 | 0.2823          | 0.9067   |
| 0.1971        | 3.65  | 4500 | 0.2933          | 0.9067   |
| 0.2164        | 3.69  | 4550 | 0.2910          | 0.9067   |
| 0.1939        | 3.73  | 4600 | 0.2813          | 0.9067   |
| 0.1834        | 3.77  | 4650 | 0.2913          | 0.9067   |
| 0.234         | 3.81  | 4700 | 0.2841          | 0.9067   |
| 0.2226        | 3.86  | 4750 | 0.2888          | 0.9067   |
| 0.2176        | 3.9   | 4800 | 0.2902          | 0.9067   |
| 0.2279        | 3.94  | 4850 | 0.2842          | 0.9067   |
| 0.1948        | 3.98  | 4900 | 0.2856          | 0.9067   |
| 0.2044        | 4.02  | 4950 | 0.2845          | 0.9067   |
| 0.2075        | 4.06  | 5000 | 0.2825          | 0.9067   |
| 0.1721        | 4.1   | 5050 | 0.2796          | 0.9067   |
| 0.2206        | 4.14  | 5100 | 0.2752          | 0.9067   |
| 0.2012        | 4.18  | 5150 | 0.2738          | 0.9067   |
| 0.1868        | 4.22  | 5200 | 0.2932          | 0.9      |
| 0.2117        | 4.26  | 5250 | 0.2881          | 0.9      |
| 0.1946        | 4.3   | 5300 | 0.2985          | 0.9      |
| 0.2138        | 4.34  | 5350 | 0.3025          | 0.8933   |
| 0.1841        | 4.38  | 5400 | 0.2906          | 0.9067   |
| 0.2171        | 4.42  | 5450 | 0.2919          | 0.9067   |
| 0.2116        | 4.46  | 5500 | 0.2889          | 0.9067   |
| 0.162         | 4.5   | 5550 | 0.2994          | 0.8933   |
| 0.1821        | 4.55  | 5600 | 0.2975          | 0.9      |
| 0.1802        | 4.59  | 5650 | 0.2994          | 0.9      |
| 0.1619        | 4.63  | 5700 | 0.2978          | 0.9      |
| 0.1955        | 4.67  | 5750 | 0.2984          | 0.9      |
| 0.2031        | 4.71  | 5800 | 0.2925          | 0.9067   |
| 0.1937        | 4.75  | 5850 | 0.2939          | 0.9067   |
| 0.1799        | 4.79  | 5900 | 0.2955          | 0.9067   |
| 0.2106        | 4.83  | 5950 | 0.2965          | 0.9067   |
| 0.196         | 4.87  | 6000 | 0.2954          | 0.9067   |
| 0.2336        | 4.91  | 6050 | 0.2932          | 0.9067   |
| 0.1805        | 4.95  | 6100 | 0.2931          | 0.9067   |
| 0.1877        | 4.99  | 6150 | 0.2935          | 0.9067   |


### Framework versions

- Transformers 4.24.0
- Pytorch 1.13.0
- Datasets 2.7.1
- Tokenizers 0.13.2
