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Model: rbelanec/train_record_42_1779354540
Source: Original Platform

.gitattributes

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README.md

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+---
+library_name: transformers
+license: llama3.2
+base_model: meta-llama/Llama-3.2-1B-Instruct
+tags:
+- peft-factory
+- freeze
+- llama-factory
+- generated_from_trainer
+model-index:
+- name: train_record_42_1779354540
+  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. -->
+
+# train_record_42_1779354540
+
+This model is a fine-tuned version of [meta-llama/Llama-3.2-1B-Instruct](https://huggingface.co/meta-llama/Llama-3.2-1B-Instruct) on the record dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.3537
+- Num Input Tokens Seen: 49166912
+
+## 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: 2e-06
+- train_batch_size: 8
+- eval_batch_size: 8
+- seed: 42
+- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
+- lr_scheduler_type: cosine
+- lr_scheduler_warmup_ratio: 0.1
+- num_epochs: 1
+
+### Training results
+
+| Training Loss | Epoch  | Step  | Validation Loss | Input Tokens Seen |
+|:-------------:|:------:|:-----:|:---------------:|:-----------------:|
+| 0.764         | 0.0501 | 782   | 0.6362          | 2474432           |
+| 0.6569        | 0.1001 | 1564  | 0.5395          | 4931328           |
+| 0.5165        | 0.1502 | 2346  | 0.5076          | 7397056           |
+| 0.5774        | 0.2002 | 3128  | 0.4884          | 9832064           |
+| 0.4226        | 0.2503 | 3910  | 0.4644          | 12304064          |
+| 0.3784        | 0.3004 | 4692  | 0.4629          | 14775488          |
+| 0.579         | 0.3504 | 5474  | 0.4391          | 17259840          |
+| 0.3547        | 0.4005 | 6256  | 0.4233          | 19707456          |
+| 0.3794        | 0.4505 | 7038  | 0.4316          | 22178432          |
+| 0.3939        | 0.5006 | 7820  | 0.4134          | 24646208          |
+| 0.3382        | 0.5507 | 8602  | 0.3985          | 27101056          |
+| 0.4           | 0.6007 | 9384  | 0.3917          | 29544576          |
+| 0.3188        | 0.6508 | 10166 | 0.3784          | 32010176          |
+| 0.4233        | 0.7009 | 10948 | 0.3722          | 34475136          |
+| 0.2995        | 0.7509 | 11730 | 0.3648          | 36931648          |
+| 0.3367        | 0.8010 | 12512 | 0.3636          | 39382144          |
+| 0.272         | 0.8510 | 13294 | 0.3571          | 41847872          |
+| 0.3451        | 0.9011 | 14076 | 0.3544          | 44318848          |
+| 0.2502        | 0.9512 | 14858 | 0.3537          | 46767552          |
+
+
+### Framework versions
+
+- Transformers 4.51.3
+- Pytorch 2.10.0+cu128
+- Datasets 4.0.0
+- Tokenizers 0.21.4

all_results.json

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+{
+    "epoch": 1.0,
+    "eval_loss": 0.3537425398826599,
+    "eval_runtime": 49.0759,
+    "eval_samples_per_second": 282.95,
+    "eval_steps_per_second": 35.374,
+    "num_input_tokens_seen": 49166912,
+    "total_flos": 2.8707953551107686e+17,
+    "train_loss": 0.44386771268258823,
+    "train_runtime": 3548.0201,
+    "train_samples_per_second": 35.222,
+    "train_steps_per_second": 4.403
+}

config.json

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+{
+  "architectures": [
+    "LlamaForCausalLM"
+  ],
+  "attention_bias": false,
+  "attention_dropout": 0.0,
+  "bos_token_id": 128000,
+  "eos_token_id": [
+    128001,
+    128008,
+    128009
+  ],
+  "head_dim": 64,
+  "hidden_act": "silu",
+  "hidden_size": 2048,
+  "initializer_range": 0.02,
+  "intermediate_size": 8192,
+  "max_position_embeddings": 131072,
+  "mlp_bias": false,
+  "model_type": "llama",
+  "num_attention_heads": 32,
+  "num_hidden_layers": 16,
+  "num_key_value_heads": 8,
+  "pretraining_tp": 1,
+  "rms_norm_eps": 1e-05,
+  "rope_scaling": {
+    "factor": 32.0,
+    "high_freq_factor": 4.0,
+    "low_freq_factor": 1.0,
+    "original_max_position_embeddings": 8192,
+    "rope_type": "llama3"
+  },
+  "rope_theta": 500000.0,
+  "tie_word_embeddings": true,
+  "torch_dtype": "bfloat16",
+  "transformers_version": "4.51.3",
+  "use_cache": false,
+  "vocab_size": 128256
+}

eval_results.json

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+{
+    "epoch": 1.0,
+    "eval_loss": 0.3537425398826599,
+    "eval_runtime": 49.0759,
+    "eval_samples_per_second": 282.95,
+    "eval_steps_per_second": 35.374,
+    "num_input_tokens_seen": 49166912
+}

generation_config.json

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+{
+  "bos_token_id": 128000,
+  "do_sample": true,
+  "eos_token_id": [
+    128001,
+    128008,
+    128009
+  ],
+  "temperature": 0.6,
+  "top_p": 0.9,
+  "transformers_version": "4.51.3"
+}

model.safetensors

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special_tokens_map.json

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+{
+  "additional_special_tokens": [
+    {
+      "content": "<|eom_id|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false
+    }
+  ],
+  "bos_token": {
+    "content": "<|begin_of_text|>",
+    "lstrip": false,
+    "normalized": false,
+    "rstrip": false,
+    "single_word": false
+  },
+  "eos_token": {
+    "content": "<|eot_id|>",
+    "lstrip": false,
+    "normalized": false,
+    "rstrip": false,
+    "single_word": false
+  },
+  "pad_token": "<|eot_id|>"
+}

train.yaml

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+seed: 42
+
+### model
+model_name_or_path: meta-llama/Llama-3.2-1B-Instruct
+trust_remote_code: true
+flash_attn: auto
+use_cache: false
+
+### method
+# Full fine-tune of every decoder block, but with the (tied) embeddings frozen.
+# `finetuning_type: freeze` only trains modules whose name matches a trainable layer;
+# embed_tokens / lm_head / final model.norm are "extra" modules and stay frozen unless
+# listed in freeze_extra_modules. Setting freeze_trainable_layers = num_hidden_layers (16
+# for Llama-3.2-1B) makes ALL decoder blocks trainable, so this == "full FT minus
+# embeddings". Because tie_word_embeddings=true, freezing embed_tokens also freezes lm_head.
+# This is lever B of the embedding-amplification fix (see figures/amplification/README.md).
+stage: sft
+do_train: true
+finetuning_type: freeze
+freeze_trainable_layers: 16
+freeze_trainable_modules: all
+# freeze_extra_modules: left unset -> embed_tokens, lm_head (tied), final norm stay frozen
+
+### dataset
+dataset: record
+template: llama3
+cutoff_len: 2048
+overwrite_cache: true
+preprocessing_num_workers: 4
+dataloader_num_workers: 4
+packing: false
+
+### output
+output_dir: saves_bts_preliminary/freeze/llama-3.2-1b-instruct/train_record_42_1779354540
+logging_steps: 5
+save_steps: 0.05
+overwrite_output_dir: true
+save_only_model: false
+plot_loss: true
+include_num_input_tokens_seen: true
+push_to_hub: true
+push_to_hub_organization: rbelanec
+load_best_model_at_end: true
+save_total_limit: 1
+
+### train
+per_device_train_batch_size: 8
+learning_rate: 2.0e-6
+num_train_epochs: 1
+weight_decay: 1.0e-2
+lr_scheduler_type: cosine
+bf16: true
+ddp_timeout: 180000000
+resume_from_checkpoint: null
+warmup_ratio: 0.1
+optim: adamw_torch
+report_to:
+- wandb
+run_name: freeze_llama-3.2-1b-instruct_train_record_42_1779354540
+
+### eval
+per_device_eval_batch_size: 8
+eval_strategy: steps
+eval_steps: 0.05
+val_size: 0.1

train_results.json

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+{
+    "epoch": 1.0,
+    "num_input_tokens_seen": 49166912,
+    "total_flos": 2.8707953551107686e+17,
+    "train_loss": 0.44386771268258823,
+    "train_runtime": 3548.0201,
+    "train_samples_per_second": 35.222,
+    "train_steps_per_second": 4.403
+}

training_args.bin

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