File size: 2,158 Bytes
7440193 ad75e5a 9dcc525 69bcbf3 5cc7705 69bcbf3 5029bc9 69bcbf3 ba2da2d 0c7ede3 ba2da2d 69bcbf3 9eddab3 69bcbf3 3ff650d 56e6ab5 69bcbf3 5a3b0b3 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 |
---
language:
- tr
tags:
- '#Turkish '
- '#turkish'
- '#gpt2'
pipeline_tag: text-generation
---
# Model Card for Model ID
gpt2 fine-tuned with Turkish corpus data.
Warning: Since the model is trained on a large dataset, it may produce unethical texts. Please be careful in this regard. No liability is accepted.
### Training Data
- Dataset size: ~5 million data (Wikipedia, News and etc.)
## Using model
```Python
from tokenizers import (decoders, models, normalizers, pre_tokenizers, processors, trainers, Tokenizer)
from transformers import GPT2Tokenizer, GPT2TokenizerFast, GPT2Model, GPT2LMHeadModel
from transformers import TextDataset, DataCollatorForLanguageModeling, Trainer, TrainingArguments
import torch
device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
print(device)
model = GPT2LMHeadModel.from_pretrained("erythropygia/gpt2-turkish-base").to(device)
tokenizer = GPT2TokenizerFast.from_pretrained("erythropygia/gpt2-turkish-base")
tokenizer.pad_token = tokenizer.eos_token
def generate_output(text):
# Input text for completion
input_text = text
# Tokenize the input text
input_ids = tokenizer.encode(input_text, return_tensors="pt").to(device)
# Generate text completions with specified parameters
output_text = model.generate(input_ids,
no_repeat_ngram_size = 3,
max_length=50,
repetition_penalty=1.1,
top_k=100,
top_p=0.7,
temperature = 0.8,
do_sample=True,
num_return_sequences=1)[0]
# Decode the generated token IDs to text
completed_text = tokenizer.decode(output_text, skip_special_tokens=False)
#print("Input Text:", input_text)
return completed_text
print(generate_output("Türkiye'nin en çok tercih "))
```
#### Training Hyperparameters
- **Epochs:** 10
- **LearningRate:** 4e-4
#### Training Results
**training_loss:** 3.5089332405925294 |