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Model: sadia72/gpt2-shakespeare
Source: Original Platform

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README.md

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+---
+license: mit
+tags:
+- generated_from_trainer
+model-index:
+- name: gpt2-shakespeare
+  results: []
+pipeline_tag: text-generation
+---
+
+<!-- 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-shakespeare
+
+This model is a fine-tuned version of [gpt2](https://huggingface.co/gpt2) on [datasets](https://github.com/sadia-sust/dataset-finetune-gpt2) containing Shakespeare Books.
+It achieves the following results on the evaluation set:
+- Loss: 2.5738
+
+## Model description
+
+GPT-2 model is finetuned with text corpus.  
+
+## Intended uses & limitations
+
+Intended use for this model is to write novel in Shakespeare Style. It has limitations to write in other writer's style.
+
+## Datasets Description
+
+Text corpus is developed for fine-tuning gpt-2 model. Books are downloaded from [Project Gutenberg](http://www.gutenberg.org/) as plain text files. 
+A large text corpus were needed to train the model to be abled to write in Shakespeare style. 
+
+
+The following books are used to develop text corpus:
+
+- Macbeth, word count: 38197
+- THE TRAGEDY OF TITUS ANDRONICUS, word count: 40413
+- King Richard II, word count: 48423
+- Shakespeare's Tragedy of Romeo and Juliet, word count: 144935
+- A MIDSUMMER NIGHT’S DREAM, word count: 36597
+- ALL’S WELL THAT ENDS WELL, word count: 49363
+- THE TRAGEDY OF HAMLET, PRINCE OF DENMARK, word count: 57471
+- THE TRAGEDY OF JULIUS CAESAR, word count: 37391
+- THE TRAGEDY OF KING LEAR, word count: 54101
+- THE LIFE AND DEATH OF KING RICHARD III, word count: 55985
+- Romeo and Juliet, word count: 51417
+- Measure for Measure, word count: 62703
+- Much Ado about Nothing, word count: 45577
+- Othello, the Moor of Venice, word count: 53967
+- THE WINTER’S TALE, word count: 52911
+- The Comedy of Errors, word count: 43179
+- The Merchant of Venice, word count: 45903
+- The Taming of the Shrew, word count: 44777
+- The Tempest, word count: 32323
+- TWELFTH NIGHT: OR, WHAT YOU WILL, word count: 42907
+- The Sonnets, word count: 39849
+
+Corpus has total 1078389 word tokens.
+
+## Datasets Preprocessing
+
+- Header text are removed manually.
+- Using sent_tokenize() function from NLTK python library, extra spaces and new-lines were removed programmatically. 
+
+
+## Training and evaluation data
+
+Training dataset has 880447 word tokens and test dataset has 197913 word tokens.
+
+## Training procedure
+
+To train the model, training api from Transformer class is used. 
+
+### Training hyperparameters
+
+The following hyperparameters were used during training:
+- learning_rate: 5e-05
+- train_batch_size: 32
+- eval_batch_size: 64
+- seed: 42
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- lr_scheduler_warmup_steps: 350
+- num_epochs: 3
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss |
+|:-------------:|:-----:|:----:|:---------------:|
+| No log        | 0.63  | 250  | 2.7133          |
+| 2.8492        | 1.25  | 500  | 2.6239          |
+| 2.8492        | 1.88  | 750  | 2.5851          |
+| 2.3842        | 2.51  | 1000 | 2.5738          |
+
+
+## Sample Code Using Transformers Pipeline
+
+```
+from transformers import pipeline
+
+story = pipeline('text-generation',model='./gpt2-shakespeare', tokenizer='gpt2', max_length = 300)
+story("how art thou")
+
+```
+
+
+### Framework versions
+
+- Transformers 4.26.1
+- Pytorch 1.13.1+cu116
+- Datasets 2.10.0
+- Tokenizers 0.13.2

config.json

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+{
+  "_name_or_path": "gpt2",
+  "activation_function": "gelu_new",
+  "architectures": [
+    "GPT2LMHeadModel"
+  ],
+  "attn_pdrop": 0.1,
+  "bos_token_id": 50256,
+  "embd_pdrop": 0.1,
+  "eos_token_id": 50256,
+  "initializer_range": 0.02,
+  "layer_norm_epsilon": 1e-05,
+  "model_type": "gpt2",
+  "n_ctx": 1024,
+  "n_embd": 768,
+  "n_head": 12,
+  "n_inner": null,
+  "n_layer": 12,
+  "n_positions": 1024,
+  "reorder_and_upcast_attn": false,
+  "resid_pdrop": 0.1,
+  "scale_attn_by_inverse_layer_idx": false,
+  "scale_attn_weights": true,
+  "summary_activation": null,
+  "summary_first_dropout": 0.1,
+  "summary_proj_to_labels": true,
+  "summary_type": "cls_index",
+  "summary_use_proj": true,
+  "task_specific_params": {
+    "text-generation": {
+      "do_sample": true,
+      "max_length": 50
+    }
+  },
+  "torch_dtype": "float32",
+  "transformers_version": "4.26.1",
+  "use_cache": true,
+  "vocab_size": 50257
+}

generation_config.json

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+{
+  "_from_model_config": true,
+  "bos_token_id": 50256,
+  "eos_token_id": 50256,
+  "transformers_version": "4.26.1"
+}

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