SmolLM-360M-Instruct_fsdp_qlora_nf4_adapter-plaba

README.md

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+---
+library_name: peft
+tags:
+- trl
+- sft
+- generated_from_trainer
+base_model: dmariko/SmolLM-360M-Instruct_qlora_nf4_merged
+datasets:
+- generator
+model-index:
+- name: SmolLM_360M_Instruct_qlora_nf4-plaba
+  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. -->
+
+# SmolLM_360M_Instruct_qlora_nf4-plaba
+
+This model is a fine-tuned version of [dmariko/SmolLM-360M-Instruct_qlora_nf4_merged](https://huggingface.co/dmariko/SmolLM-360M-Instruct_qlora_nf4_merged) on the generator dataset.
+It achieves the following results on the evaluation set:
+- Loss: 1.7869
+
+## 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: 0.001
+- train_batch_size: 4
+- eval_batch_size: 4
+- seed: 42
+- distributed_type: multi-GPU
+- num_devices: 8
+- gradient_accumulation_steps: 8
+- total_train_batch_size: 256
+- total_eval_batch_size: 32
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: cosine
+- lr_scheduler_warmup_ratio: 0.03
+- num_epochs: 10
+
+### Training results
+
+| Training Loss | Epoch  | Step | Validation Loss |
+|:-------------:|:------:|:----:|:---------------:|
+| No log        | 0.8889 | 1    | 1.8457          |
+| No log        | 1.7778 | 2    | 1.8424          |
+| No log        | 2.6667 | 3    | 1.8318          |
+| No log        | 3.5556 | 4    | 1.8130          |
+| No log        | 4.4444 | 5    | 1.7966          |
+| No log        | 5.3333 | 6    | 1.7906          |
+| No log        | 6.2222 | 7    | 1.7891          |
+| No log        | 8.0    | 9    | 1.7869          |
+| 1.8097        | 8.8889 | 10   | 1.7869          |
+
+
+### Framework versions
+
+- PEFT 0.10.0
+- Transformers 4.40.0
+- Pytorch 2.1.0
+- Datasets 2.18.0
+- Tokenizers 0.19.1

adapter_config.json

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+{
+  "alpha_pattern": {},
+  "auto_mapping": null,
+  "base_model_name_or_path": "dmariko/SmolLM-360M-Instruct_qlora_nf4_merged",
+  "bias": "none",
+  "fan_in_fan_out": false,
+  "inference_mode": true,
+  "init_lora_weights": true,
+  "layer_replication": null,
+  "layers_pattern": null,
+  "layers_to_transform": null,
+  "loftq_config": {},
+  "lora_alpha": 8,
+  "lora_dropout": 0.05,
+  "megatron_config": null,
+  "megatron_core": "megatron.core",
+  "modules_to_save": null,
+  "peft_type": "LORA",
+  "r": 16,
+  "rank_pattern": {},
+  "revision": null,
+  "target_modules": [
+    "up_proj",
+    "k_proj",
+    "o_proj",
+    "v_proj",
+    "down_proj",
+    "q_proj",
+    "gate_proj"
+  ],
+  "task_type": "CAUSAL_LM",
+  "use_dora": false,
+  "use_rslora": false
+}

adapter_model.safetensors

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runs/Sep04_17-08-41_algo-1/events.out.tfevents.1725469763.algo-1.67.0

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special_tokens_map.json

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+    "content": "<|endoftext|>",
+    "lstrip": false,
+    "normalized": false,
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+    "single_word": false
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+}

tokenizer_config.json

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+}

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