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recreate_llama_68M_vanilla

Text Generation
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  1. README.md +68 -3
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README.md CHANGED
@@ -1,3 +1,68 @@
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- ---
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- license: apache-2.0
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- ---
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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+ ---
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+ license: apache-2.0
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+ base_model: JackFram/llama-68m
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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: recreate_llama_68M_vanilla
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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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+ # recreate_llama_68M_vanilla
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+
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+ This model is a fine-tuned version of [JackFram/llama-68m](https://huggingface.co/JackFram/llama-68m) on an unknown dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 1.6571
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+ - Accuracy: 0.6944
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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: 0.0005
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+ - train_batch_size: 32
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+ - eval_batch_size: 16
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+ - seed: 42
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+ - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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+ - lr_scheduler_type: linear
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+ - num_epochs: 3.0
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+
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+ ### Training results
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+
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+ | Training Loss | Epoch | Step | Validation Loss | Accuracy |
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+ |:-------------:|:------:|:----:|:---------------:|:--------:|
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+ | No log | 0.3125 | 10 | 2.1108 | 0.6368 |
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+ | No log | 0.625 | 20 | 1.8348 | 0.6696 |
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+ | No log | 0.9375 | 30 | 1.7489 | 0.6794 |
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+ | No log | 1.25 | 40 | 1.7315 | 0.6781 |
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+ | No log | 1.5625 | 50 | 1.6956 | 0.6846 |
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+ | No log | 1.875 | 60 | 1.6770 | 0.6873 |
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+ | No log | 2.1875 | 70 | 1.6866 | 0.6903 |
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+ | No log | 2.5 | 80 | 1.6705 | 0.6911 |
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+ | No log | 2.8125 | 90 | 1.6571 | 0.6944 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.41.0.dev0
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+ - Pytorch 2.1.0+cu121
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+ - Datasets 2.19.1
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+ - Tokenizers 0.19.1
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+ {
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+ "epoch": 3.0,
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+ "eval_accuracy": 0.6942843185148998,
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+ "eval_loss": 1.6576473712921143,
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+ "eval_runtime": 2.7252,
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+ "eval_samples": 10,
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+ "eval_samples_per_second": 3.669,
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+ "eval_steps_per_second": 0.367,
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+ "perplexity": 5.246952182142712,
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+ "total_flos": 1601895923712000.0,
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+ "train_loss": 1.7650197347005208,
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+ "train_runtime": 162.5074,
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+ "train_samples": 1000,
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+ "train_samples_per_second": 18.461,
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+ "train_steps_per_second": 0.591
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+ }
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+ {
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+ "architectures": [
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+ "LlamaForCausalLM"
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+ ],
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+ "attention_bias": false,
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+ "use_cache": true,
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+ "vocab_size": 32000
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+ }
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