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--- |
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license: apache-2.0 |
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tags: |
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- generated_from_trainer |
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- text-generation |
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- opt |
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- non-commercial |
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widget: |
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- text: "If you could live anywhere, where would it be? peter szemraj:" |
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example_title: "live anywhere" |
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- text: "What would you sing at Karaoke night? peter szemraj:" |
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example_title: "Karaoke" |
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- text: "If you could hire someone to help you, would it be with cleaning, cooking, or yard work? peter szemraj:" |
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example_title: "help" |
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- text: "What form of public transportation do you prefer? (air, boat, train, bus, car, etc.) peter szemraj:" |
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example_title: "transportation" |
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- text: "What's your favorite zoo animal? peter szemraj:" |
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example_title: "animal" |
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- text: "Do you like or dislike surprises? Why or why not? peter szemraj:" |
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example_title: "surprises" |
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- text: "What celebrity would you like to meet at Starbucks for a cup of coffee? peter szemraj:" |
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example_title: "celebrity " |
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inference: |
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parameters: |
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min_length: 2 |
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max_length: 64 |
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length_penalty: 0.7 |
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temperature: 0.65 |
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no_repeat_ngram_size: 2 |
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top_k: 20 |
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do_sample: True |
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repetition_penalty: 4.5 |
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--- |
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# opt-peter-1pt3B-1E-ps_DS-msgs_Ep-2_Bs-4 |
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This model is a fine-tuned version of [pszemraj/opt-peter-1.3B-1E](https://huggingface.co/pszemraj/opt-peter-1.3B-1E) on 80k Whatsapp/iMessages (mine). |
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It achieves the following results on the evaluation set: |
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- eval_loss: 3.4220 |
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- eval_runtime: 954.9678 |
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- eval_samples_per_second: 9.114 |
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- eval_steps_per_second: 2.279 |
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- epoch: 1.0 |
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- step: 1235 |
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## Model description |
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- Exploring to see how OPT does in terms of dialogue/conversational applications |
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- Seems to do a lot better than GPT-Neo with similar training parameters |
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## Intended uses & limitations |
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- OPT has a license that does not allow for commercial use, see original for details |
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- **any statements or claims made by this model do not reflect actual claims/statements by me** |
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## Training and evaluation data |
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More information needed |
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## Training procedure |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- learning_rate: 3e-05 |
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- train_batch_size: 4 |
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- eval_batch_size: 4 |
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- seed: 42 |
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- distributed_type: multi-GPU |
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- gradient_accumulation_steps: 16 |
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- total_train_batch_size: 64 |
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: cosine |
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- lr_scheduler_warmup_ratio: 0.01 |
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- num_epochs: 2 |
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### Framework versions |
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- Transformers 4.19.2 |
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- Pytorch 1.11.0+cu113 |
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- Tokenizers 0.12.1 |
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