README.md

README.md

@@ -1,74 +0,0 @@
----
-license: mit
-tags:
-- generated_from_trainer
-datasets:
-- imdb
-metrics:
-- accuracy
-model-index:
-- name: gpt2-imdb-sentiment-classifier
-  results:
-  - task:
-      name: Text Classification
-      type: text-classification
-    dataset:
-      name: imdb
-      type: imdb
-      args: plain_text
-    metrics:
-    - name: Accuracy
-      type: accuracy
-      value: 0.9394
----
-
-<!-- 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. -->
-
-# gpt2-imdb-sentiment-classifier
-
-This model is a fine-tuned version of [gpt2](https://huggingface.co/gpt2) on the imdb dataset.
-It achieves the following results on the evaluation set:
-- Loss: 0.1703
-- Accuracy: 0.9394
-
-## Model description
-
-More information needed
-
-## Intended uses & limitations
-
-This is comparable to [distilbert-imdb](https://huggingface.co/lvwerra/distilbert-imdb) and trained with exactly the same [script](https://huggingface.co/lvwerra/distilbert-imdb/blob/main/distilbert-imdb-training.ipynb)
-
-It achieves slightly lower loss (0.1703 vs 0.1903) and slightly higher accuracy (0.9394 vs 0.928)
-
-## Training and evaluation data
-
-More information needed
-
-## Training procedure
-
-### Training hyperparameters
-
-The following hyperparameters were used during training:
-- learning_rate: 5e-05
-- train_batch_size: 16
-- eval_batch_size: 16
-- seed: 42
-- 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 |
-|:-------------:|:-----:|:----:|:---------------:|:--------:|
-| 0.1967        | 1.0   | 1563 | 0.1703          | 0.9394   |
-
-
-### Framework versions
-
-- Transformers 4.18.0
-- Pytorch 1.13.1+cu117
-- Datasets 2.9.0
-- Tokenizers 0.12.1