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README.md

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+---
+license: other
+base_model: meta-llama/Meta-Llama-3-8B
+tags:
+- llama-factory
+- full
+- generated_from_trainer
+model-index:
+- name: C021_random_sample_llama3-8b-base_pretrain_20240505_135320
+  results: []
+---
+
+<!-- This model card has been generated automatically according to the information the Trainer had access to. You
+should probably proofread and complete it, then remove this comment. -->
+
+# C021_random_sample_llama3-8b-base_pretrain_20240505_135320
+
+This model is a fine-tuned version of [/data/pro-align/progressalign/shared_storage/downloaded_models/llama3-8b-base](https://huggingface.co//data/pro-align/progressalign/shared_storage/downloaded_models/llama3-8b-base) on the C021_random_sample_data dataset.
+It achieves the following results on the evaluation set:
+- Loss: 1.2184
+
+## 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: 1.5e-05
+- train_batch_size: 4
+- eval_batch_size: 8
+- seed: 42
+- distributed_type: multi-GPU
+- num_devices: 8
+- total_train_batch_size: 32
+- total_eval_batch_size: 64
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: polynomial
+- lr_scheduler_warmup_steps: 20
+- num_epochs: 4.0
+- mixed_precision_training: Native AMP
+
+### Training results
+
+| Training Loss | Epoch  | Step | Validation Loss |
+|:-------------:|:------:|:----:|:---------------:|
+| 1.2572        | 0.4264 | 200  | 1.2612          |
+| 1.1754        | 0.8529 | 400  | 1.2226          |
+| 1.1662        | 1.2793 | 600  | 1.2202          |
+| 1.1182        | 1.7058 | 800  | 1.2184          |
+| 1.046         | 2.1322 | 1000 | 1.2190          |
+| 1.0772        | 2.5586 | 1200 | 1.2190          |
+| 1.0326        | 2.9851 | 1400 | 1.2188          |
+| 1.013         | 3.4115 | 1600 | 1.2191          |
+| 1.1103        | 3.8380 | 1800 | 1.2188          |
+
+
+### Framework versions
+
+- Transformers 4.40.1
+- Pytorch 2.3.0
+- Datasets 2.19.0
+- Tokenizers 0.19.1

all_results.json

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+{
+    "epoch": 4.0,
+    "eval_loss": 1.2184005975723267,
+    "eval_runtime": 87.9641,
+    "eval_samples_per_second": 18.951,
+    "eval_steps_per_second": 0.307,
+    "perplexity": 3.3817745873907485,
+    "total_flos": 391958715432960.0,
+    "train_loss": 1.1227505109203395,
+    "train_runtime": 12501.281,
+    "train_samples_per_second": 4.798,
+    "train_steps_per_second": 0.15
+}

config.json

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+{
+  "_name_or_path": "/data/pro-align/progressalign/shared_storage/downloaded_models/llama3-8b-base",
+  "architectures": [
+    "LlamaForCausalLM"
+  ],
+  "attention_bias": false,
+  "attention_dropout": 0.0,
+  "bos_token_id": 128000,
+  "eos_token_id": 128001,
+  "hidden_act": "silu",
+  "hidden_size": 4096,
+  "initializer_range": 0.02,
+  "intermediate_size": 14336,
+  "max_position_embeddings": 8192,
+  "model_type": "llama",
+  "num_attention_heads": 32,
+  "num_hidden_layers": 32,
+  "num_key_value_heads": 8,
+  "pretraining_tp": 1,
+  "rms_norm_eps": 1e-05,
+  "rope_scaling": null,
+  "rope_theta": 500000.0,
+  "tie_word_embeddings": false,
+  "torch_dtype": "float16",
+  "transformers_version": "4.40.1",
+  "use_cache": false,
+  "vocab_size": 128256
+}

eval_results.json

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+{
+    "epoch": 4.0,
+    "eval_loss": 1.2184005975723267,
+    "eval_runtime": 87.9641,
+    "eval_samples_per_second": 18.951,
+    "eval_steps_per_second": 0.307,
+    "perplexity": 3.3817745873907485
+}

generation_config.json

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+{
+  "_from_model_config": true,
+  "bos_token_id": 128000,
+  "eos_token_id": 128001,
+  "transformers_version": "4.40.1"
+}

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special_tokens_map.json

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tokenizer_config.json

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