readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  metrics:
  - accuracy
  - precision
  - recall
  - f1
  model-index:
  - name: distilbert-base-uncased-sentiment-finetuned-memes-30epochs
    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. -->
  
  # distilbert-base-uncased-sentiment-finetuned-memes-30epochs
  
  This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the None dataset.
  It achieves the following results on the evaluation set:
  - Loss: 1.8839
  - Accuracy: 0.8365
  - Precision: 0.8373
  - Recall: 0.8365
  - F1: 0.8368
  
  ## 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: 8
  - eval_batch_size: 8
  - seed: 42
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: linear
  - num_epochs: 30
  
  ### Training results
  
  | Training Loss | Epoch | Step  | Validation Loss | Accuracy | Precision | Recall | F1     |
  |:-------------:|:-----:|:-----:|:---------------:|:--------:|:---------:|:------:|:------:|
  | 0.4774        | 1.0   | 2147  | 0.4463          | 0.7453   | 0.7921    | 0.7453 | 0.7468 |
  | 0.4036        | 2.0   | 4294  | 0.5419          | 0.7835   | 0.8072    | 0.7835 | 0.7858 |
  | 0.3163        | 3.0   | 6441  | 0.6776          | 0.7982   | 0.7970    | 0.7982 | 0.7954 |
  | 0.2613        | 4.0   | 8588  | 0.6988          | 0.7966   | 0.7953    | 0.7966 | 0.7956 |
  | 0.229         | 5.0   | 10735 | 0.8523          | 0.8003   | 0.8033    | 0.8003 | 0.8013 |
  | 0.1893        | 6.0   | 12882 | 1.0472          | 0.8056   | 0.8166    | 0.8056 | 0.8074 |
  | 0.1769        | 7.0   | 15029 | 1.0321          | 0.8150   | 0.8193    | 0.8150 | 0.8161 |
  | 0.1648        | 8.0   | 17176 | 1.1623          | 0.8129   | 0.8159    | 0.8129 | 0.8138 |
  | 0.1366        | 9.0   | 19323 | 1.1932          | 0.8255   | 0.8257    | 0.8255 | 0.8256 |
  | 0.1191        | 10.0  | 21470 | 1.2308          | 0.8349   | 0.8401    | 0.8349 | 0.8361 |
  | 0.1042        | 11.0  | 23617 | 1.3166          | 0.8297   | 0.8288    | 0.8297 | 0.8281 |
  | 0.0847        | 12.0  | 25764 | 1.3542          | 0.8286   | 0.8278    | 0.8286 | 0.8280 |
  | 0.0785        | 13.0  | 27911 | 1.3925          | 0.8291   | 0.8293    | 0.8291 | 0.8292 |
  | 0.0674        | 14.0  | 30058 | 1.4191          | 0.8255   | 0.8307    | 0.8255 | 0.8267 |
  | 0.0694        | 15.0  | 32205 | 1.5601          | 0.8255   | 0.8281    | 0.8255 | 0.8263 |
  | 0.0558        | 16.0  | 34352 | 1.6110          | 0.8265   | 0.8302    | 0.8265 | 0.8275 |
  | 0.045         | 17.0  | 36499 | 1.5730          | 0.8270   | 0.8303    | 0.8270 | 0.8280 |
  | 0.0436        | 18.0  | 38646 | 1.6081          | 0.8365   | 0.8361    | 0.8365 | 0.8363 |
  | 0.028         | 19.0  | 40793 | 1.5569          | 0.8375   | 0.8371    | 0.8375 | 0.8373 |
  | 0.0262        | 20.0  | 42940 | 1.6976          | 0.8286   | 0.8324    | 0.8286 | 0.8296 |
  | 0.0183        | 21.0  | 45087 | 1.6368          | 0.8333   | 0.8354    | 0.8333 | 0.8340 |
  | 0.0225        | 22.0  | 47234 | 1.7570          | 0.8318   | 0.8357    | 0.8318 | 0.8328 |
  | 0.0118        | 23.0  | 49381 | 1.7233          | 0.8360   | 0.8369    | 0.8360 | 0.8363 |
  | 0.0152        | 24.0  | 51528 | 1.8027          | 0.8360   | 0.8371    | 0.8360 | 0.8364 |
  | 0.0079        | 25.0  | 53675 | 1.7908          | 0.8412   | 0.8423    | 0.8412 | 0.8416 |
  | 0.0102        | 26.0  | 55822 | 1.8247          | 0.8344   | 0.8339    | 0.8344 | 0.8341 |
  | 0.0111        | 27.0  | 57969 | 1.8123          | 0.8391   | 0.8394    | 0.8391 | 0.8392 |
  | 0.0078        | 28.0  | 60116 | 1.8630          | 0.8354   | 0.8352    | 0.8354 | 0.8353 |
  | 0.0058        | 29.0  | 62263 | 1.8751          | 0.8339   | 0.8343    | 0.8339 | 0.8341 |
  | 0.0028        | 30.0  | 64410 | 1.8839          | 0.8365   | 0.8373    | 0.8365 | 0.8368 |
  
  
  ### Framework versions
  
  - Transformers 4.13.0.dev0
  - Pytorch 1.11.0+cu102
  - Datasets 1.15.2.dev0
  - Tokenizers 0.10.1
  