SmolLM-1.7B-Instruct-dpo-16k

README.md

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+---
+license: apache-2.0
+base_model: HuggingFaceTB/SmolLM-360M-Instruct
+tags:
+- trl
+- dpo
+- generated_from_trainer
+model-index:
+- name: SmolLM-1.7B-Instruct-dpo-16k
+  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-1.7B-Instruct-dpo-16k
+
+This model is a fine-tuned version of [HuggingFaceTB/SmolLM-360M-Instruct](https://huggingface.co/HuggingFaceTB/SmolLM-360M-Instruct) on an unknown dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.8854
+- Rewards/chosen: 0.0056
+- Rewards/rejected: 0.3516
+- Rewards/accuracies: 0.0326
+- Rewards/margins: -0.3460
+- Logps/rejected: -470.7809
+- Logps/chosen: -546.0043
+- Logits/rejected: 0.3165
+- Logits/chosen: 0.6158
+
+## 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: 5e-06
+- train_batch_size: 2
+- eval_batch_size: 2
+- seed: 42
+- gradient_accumulation_steps: 2
+- total_train_batch_size: 4
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: cosine
+- lr_scheduler_warmup_steps: 2
+- num_epochs: 6
+
+### Training results
+
+| Training Loss | Epoch  | Step  | Validation Loss | Rewards/chosen | Rewards/rejected | Rewards/accuracies | Rewards/margins | Logps/rejected | Logps/chosen | Logits/rejected | Logits/chosen |
+|:-------------:|:------:|:-----:|:---------------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------:|:------------:|:---------------:|:-------------:|
+| 0.5228        | 0.9999 | 3368  | 0.8697          | 0.0208         | 0.3405           | 0.0348             | -0.3197         | -470.8920      | -545.8519    | 0.3270          | 0.6295        |
+| 0.4508        | 2.0    | 6737  | 0.8870          | 0.0130         | 0.3621           | 0.0228             | -0.3491         | -470.6755      | -545.9296    | 0.2662          | 0.5778        |
+| 0.4451        | 2.9999 | 10105 | 0.8871          | 0.0057         | 0.3546           | 0.0337             | -0.3489         | -470.7502      | -546.0029    | 0.2855          | 0.5938        |
+| 0.4447        | 4.0    | 13474 | 0.8869          | 0.0098         | 0.3588           | 0.0196             | -0.3490         | -470.7085      | -545.9620    | 0.3198          | 0.6222        |
+| 0.4446        | 4.9999 | 16842 | 0.8870          | 0.0065         | 0.3551           | 0.0391             | -0.3486         | -470.7452      | -545.9945    | 0.3097          | 0.6124        |
+| 0.4448        | 5.9991 | 20208 | 0.8854          | 0.0056         | 0.3516           | 0.0326             | -0.3460         | -470.7809      | -546.0043    | 0.3165          | 0.6158        |
+
+
+### Framework versions
+
+- Transformers 4.41.0
+- Pytorch 2.2.0
+- Datasets 2.19.1
+- Tokenizers 0.19.1

config.json

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+{
+  "_name_or_path": "HuggingFaceTB/SmolLM-360M-Instruct",
+  "architectures": [
+    "LlamaForCausalLM"
+  ],
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+  "attention_dropout": 0.0,
+  "bos_token_id": 1,
+  "eos_token_id": 2,
+  "hidden_act": "silu",
+  "hidden_size": 960,
+  "initializer_range": 0.02,
+  "intermediate_size": 2560,
+  "max_position_embeddings": 2048,
+  "mlp_bias": false,
+  "model_type": "llama",
+  "num_attention_heads": 15,
+  "num_hidden_layers": 32,
+  "num_key_value_heads": 5,
+  "pad_token_id": 2,
+  "pretraining_tp": 1,
+  "rms_norm_eps": 1e-05,
+  "rope_scaling": null,
+  "rope_theta": 10000.0,
+  "tie_word_embeddings": true,
+  "torch_dtype": "bfloat16",
+  "transformers_version": "4.41.0",
+  "use_cache": false,
+  "vocab_size": 49152
+}

generation_config.json

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+  "eos_token_id": 2,
+  "max_new_tokens": 40,
+  "pad_token_id": 2,
+  "transformers_version": "4.41.0"
+}

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