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  1. README.md +61 -3
  2. all_results.json +16 -0
  3. checkpoint-120/config.json +41 -0
  4. checkpoint-120/generation_config.json +7 -0
  5. checkpoint-120/merges.txt +0 -0
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  9. checkpoint-120/scaler.pt +3 -0
  10. checkpoint-120/scheduler.pt +3 -0
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  14. checkpoint-120/trainer_state.json +40 -0
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  16. checkpoint-120/vocab.json +0 -0
  17. checkpoint-60/config.json +41 -0
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  32. eval_results.json +10 -0
  33. generation_config.json +7 -0
  34. merges.txt +0 -0
  35. model.safetensors +3 -0
  36. runs/Feb16_14-45-43_df2b3a150539/events.out.tfevents.1739717156.df2b3a150539.2366.0 +3 -0
  37. runs/Feb16_14-45-43_df2b3a150539/events.out.tfevents.1739718419.df2b3a150539.2366.1 +3 -0
  38. runs/Feb16_15-18-11_df2b3a150539/events.out.tfevents.1739719100.df2b3a150539.10649.0 +3 -0
  39. runs/Feb16_15-18-11_df2b3a150539/events.out.tfevents.1739721246.df2b3a150539.10649.1 +3 -0
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  41. tokenizer.json +0 -0
  42. tokenizer_config.json +59 -0
  43. train_results.json +9 -0
  44. trainer_state.json +49 -0
  45. training_args.bin +3 -0
  46. vocab.json +0 -0
README.md CHANGED
@@ -1,3 +1,61 @@
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- ---
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- license: mit
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- ---
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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+ ---
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+ library_name: transformers
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+ base_model: ai-forever/rugpt3small_based_on_gpt2
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+ tags:
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+ - generated_from_trainer
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+ metrics:
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+ - accuracy
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+ model-index:
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+ - name: aristototle_interface
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+ results: []
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+ ---
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+
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+ <!-- This model card has been generated automatically according to the information the Trainer had access to. You
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+ should probably proofread and complete it, then remove this comment. -->
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+
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+ # aristototle_interface
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+
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+ This model is a fine-tuned version of [ai-forever/rugpt3small_based_on_gpt2](https://huggingface.co/ai-forever/rugpt3small_based_on_gpt2) on an unknown dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 3.0259
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+ - Accuracy: 0.4040
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+
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+ ## Model description
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+
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+ More information needed
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+
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+ ## Intended uses & limitations
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+
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+ More information needed
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+
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+ ## Training and evaluation data
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+
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+ More information needed
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+
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+ ## Training procedure
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+
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+ ### Training hyperparameters
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+
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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: 8
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+ - eval_batch_size: 8
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+ - seed: 42
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+ - gradient_accumulation_steps: 8
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+ - total_train_batch_size: 64
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+ - optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
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+ - lr_scheduler_type: linear
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+ - lr_scheduler_warmup_steps: 500
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+ - num_epochs: 30.0
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+ - mixed_precision_training: Native AMP
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+
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+ ### Training results
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+
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.49.0.dev0
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+ - Pytorch 2.5.1+cu124
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+ - Datasets 3.3.0
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+ - Tokenizers 0.21.0
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+ "eval_samples_per_second": 8.08,
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+ "eval_steps_per_second": 8.08,
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+ "perplexity": 20.612515844582727,
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+ "train_loss": 3.8146740595499673,
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+ "train_samples_per_second": 4.072,
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+ "train_steps_per_second": 0.056
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+ }
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