SihyunPark
commited on
Commit
•
09149a1
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Parent(s):
02dcf5f
Upload folder using huggingface_hub
Browse files- .gitattributes +1 -0
- README.md +65 -0
- all_results.json +13 -0
- config.json +29 -0
- eval_results.json +8 -0
- generation_config.json +9 -0
- model-00001-of-00007.safetensors +3 -0
- model-00002-of-00007.safetensors +3 -0
- model-00003-of-00007.safetensors +3 -0
- model-00004-of-00007.safetensors +3 -0
- model-00005-of-00007.safetensors +3 -0
- model-00006-of-00007.safetensors +3 -0
- model-00007-of-00007.safetensors +3 -0
- model.safetensors.index.json +298 -0
- special_tokens_map.json +23 -0
- tokenizer.json +3 -0
- tokenizer_config.json +0 -0
- train_results.json +8 -0
- trainer_log.jsonl +4 -0
- trainer_state.json +63 -0
- training_args.bin +3 -0
- training_loss.png +0 -0
.gitattributes
CHANGED
@@ -33,3 +33,4 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
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*.zip filter=lfs diff=lfs merge=lfs -text
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*.zst filter=lfs diff=lfs merge=lfs -text
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*tfevents* filter=lfs diff=lfs merge=lfs -text
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*.zip filter=lfs diff=lfs merge=lfs -text
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*.zst filter=lfs diff=lfs merge=lfs -text
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*tfevents* filter=lfs diff=lfs merge=lfs -text
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tokenizer.json filter=lfs diff=lfs merge=lfs -text
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README.md
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---
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license: other
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base_model: wisenut-nlp-team/wisenut-llama-3-8B-vocab-expansion-pretrain
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tags:
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- llama-factory
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- full
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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: vocab_exp
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results: []
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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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# vocab_exp
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This model is a fine-tuned version of [wisenut-nlp-team/wisenut-llama-3-8B-vocab-expansion-pretrain](https://huggingface.co/wisenut-nlp-team/wisenut-llama-3-8B-vocab-expansion-pretrain) on the data_recipe_v2_10k dataset.
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It achieves the following results on the evaluation set:
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- Loss: 1.2294
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- Accuracy: 0.7120
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## Model description
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More information needed
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## Intended uses & limitations
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More information needed
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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: 5e-05
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- train_batch_size: 1
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- eval_batch_size: 1
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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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- gradient_accumulation_steps: 16
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- total_train_batch_size: 256
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- total_eval_batch_size: 16
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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_steps: 20
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- num_epochs: 1.0
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### Training results
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### Framework versions
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- Transformers 4.42.3
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- Pytorch 2.3.1+cu121
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- Datasets 2.20.0
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- Tokenizers 0.19.1
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all_results.json
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{
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"epoch": 0.9946714031971581,
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"eval_accuracy": 0.7119721949778046,
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"eval_loss": 1.2293928861618042,
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"eval_runtime": 60.1576,
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"eval_samples_per_second": 16.623,
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"eval_steps_per_second": 1.047,
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"total_flos": 1.0171584618692608e+16,
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"train_samples_per_second": 4.871,
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"train_steps_per_second": 0.019
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}
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config.json
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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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"attention_dropout": 0.0,
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"hidden_size": 4096,
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"max_position_embeddings": 8192,
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"mlp_bias": false,
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"model_type": "llama",
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"num_attention_heads": 32,
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"num_hidden_layers": 32,
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"num_key_value_heads": 8,
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"pretraining_tp": 1,
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"rms_norm_eps": 1e-05,
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"rope_scaling": null,
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"rope_theta": 500000.0,
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"tie_word_embeddings": false,
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"torch_dtype": "float32",
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"transformers_version": "4.42.3",
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"use_cache": false,
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"vocab_size": 154335
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}
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eval_results.json
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"eval_samples_per_second": 16.623,
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"eval_steps_per_second": 1.047
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}
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generation_config.json
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