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Add HuggingFaceH4/starcoder2-15b-ift-v5.0 checkpoint

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  1. README.md +71 -0
  2. added_tokens.json +4 -0
  3. all_results.json +14 -0
  4. config.json +31 -0
  5. eval_results.json +9 -0
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  34. special_tokens_map.json +28 -0
  35. tokenizer.json +0 -0
  36. tokenizer_config.json +338 -0
  37. train_results.json +8 -0
  38. trainer_state.json +3883 -0
  39. training_args.bin +3 -0
  40. vocab.json +0 -0
README.md ADDED
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+ ---
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+ license: bigcode-openrail-m
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+ base_model: bigcode/starcoder2-15b
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+ tags:
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+ - alignment-handbook
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+ - generated_from_trainer
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+ datasets:
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+ - HuggingFaceH4/airoboros-3.2
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+ - HuggingFaceH4/Code-Feedback
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+ - HuggingFaceH4/orca-math-word-problems-200k
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+ - HuggingFaceH4/SystemChat
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+ - HuggingFaceH4/capybara
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+ model-index:
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+ - name: starcoder2-15b-sft-v5.0
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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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+ # starcoder2-15b-sft-v5.0
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+
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+ This model is a fine-tuned version of [bigcode/starcoder2-15b](https://huggingface.co/bigcode/starcoder2-15b) on the HuggingFaceH4/airoboros-3.2, the HuggingFaceH4/Code-Feedback, the HuggingFaceH4/orca-math-word-problems-200k, the HuggingFaceH4/SystemChat and the HuggingFaceH4/capybara datasets.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.6614
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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: 2e-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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+ - distributed_type: multi-GPU
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+ - num_devices: 16
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+ - total_train_batch_size: 128
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+ - total_eval_batch_size: 128
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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: 0.1
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+ - num_epochs: 3
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+
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+ ### Training results
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+
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+ | Training Loss | Epoch | Step | Validation Loss |
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+ |:-------------:|:-----:|:----:|:---------------:|
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+ | 0.6422 | 1.0 | 910 | 0.6910 |
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+ | 0.5701 | 2.0 | 1820 | 0.6639 |
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+ | 0.5227 | 3.0 | 2730 | 0.6614 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.39.0.dev0
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+ - Pytorch 2.1.2+cu121
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+ - Datasets 2.16.1
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+ - Tokenizers 0.15.1
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+ {
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+ "epoch": 3.0,
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+ "eval_loss": 0.6613607406616211,
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+ "eval_runtime": 13.2548,
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+ "eval_samples": 3200,
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+ "eval_samples_per_second": 103.962,
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+ "eval_steps_per_second": 0.83,
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+ "perplexity": 1.9374268770613925,
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+ "train_loss": 0.6159939037574517,
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+ "train_runtime": 13745.4884,
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+ "train_samples": 344926,
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+ "train_samples_per_second": 25.399,
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+ "train_steps_per_second": 0.199
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+ }
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+ {
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+ "_name_or_path": "bigcode/starcoder2-15b",
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+ "architectures": [
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+ "Starcoder2ForCausalLM"
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+ ],
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+ "attention_dropout": 0.1,
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+ "bos_token_id": 0,
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+ "embedding_dropout": 0.1,
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+ "hidden_act": "gelu_pytorch_tanh",
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+ "norm_epsilon": 1e-05,
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+ "num_key_value_heads": 4,
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+ "residual_dropout": 0.1,
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+ }
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