# Load model directly
from transformers import AutoTokenizer, AutoModelForSeq2SeqLM
tokenizer = AutoTokenizer.from_pretrained("ravinderbrai/pegasus-individual-reviews")
model = AutoModelForSeq2SeqLM.from_pretrained("ravinderbrai/pegasus-individual-reviews", device_map="auto")Quick Links
pegasus-individual-reviews
This model is a fine-tuned version of google/pegasus-cnn_dailymail on the None dataset. It achieves the following results on the evaluation set:
- Loss: 3.5084
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: 5e-05
- train_batch_size: 2
- eval_batch_size: 2
- seed: 42
- gradient_accumulation_steps: 16
- total_train_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| No log | 1.0 | 1 | 3.6003 |
| No log | 2.0 | 2 | 3.5325 |
| No log | 2.29 | 3 | 3.5084 |
Framework versions
- Transformers 4.34.1
- Pytorch 2.1.0
- Datasets 2.12.0
- Tokenizers 0.14.1
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Model tree for ravinderbrai/pegasus-individual-reviews
Base model
google/pegasus-cnn_dailymail
# Use a pipeline as a high-level helper # Warning: Pipeline type "summarization" is no longer supported in transformers v5. # You must load the model directly (see below) or downgrade to v4.x with: # 'pip install "transformers<5.0.0' from transformers import pipeline pipe = pipeline("summarization", model="ravinderbrai/pegasus-individual-reviews")