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Model: lomahony/pythia-70m-helpful-dpo
Source: Original Platform

.gitattributes

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+*.arrow filter=lfs diff=lfs merge=lfs -text
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README.md

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+---
+language:
+- en
+tags:
+- pytorch
+- causal-lm
+- pythia
+license: apache-2.0
+datasets:
+- Anthropic/hh-rlhf
+---
+
+[Pythia-70m](https://huggingface.co/EleutherAI/pythia-70m) finetuned using original DPO code with the helpful subset of [Anthropic-hh-rlhf dataset](https://huggingface.co/datasets/Anthropic/hh-rlhf) for 1 epoch. 
+
+Checkpoints are also uploaded. 
+
+Fully reproducible finetuning code is available on [GitHub](https://github.com/lauraaisling/direct-preference-optimization/tree/main)
+
+[wandb log](https://wandb.ai/lauraomahony999/pythia-dpo/runs/wc2q2vp1)
+
+See [Pythia-70m](https://huggingface.co/EleutherAI/pythia-70m) for model details [(paper)](https://arxiv.org/abs/2101.00027). 
+
+See further details of these models in the paper [Attributing Mode Collapse in the Fine-Tuning of Large Language Models](https://openreview.net/pdf?id=3pDMYjpOxk).
+
+You can cite these models if they are helpful as follows: 
+
+<pre>
+@inproceedings{o2024attributing,
+  title={Attributing Mode Collapse in the Fine-Tuning of Large Language Models},
+  author={O’Mahony, Laura and Grinsztajn, Leo and Schoelkopf, Hailey and Biderman, Stella},
+  booktitle={ICLR 2024, Mathematical and Empirical Understanding of Foundation Models (ME-FoMo) workshop},
+  year={2024}
+}
+</pre>
+
+hf (pretrained=lomahony/pythia-70m-helpful-dpo), gen_kwargs: (None), limit: None, num_fewshot: 0, batch_size: 16
+|    Tasks     |Version|Filter|n-shot|    Metric     |  Value  |   | Stderr |
+|--------------|------:|------|-----:|---------------|--------:|---|--------|
+|arc_challenge |      1|none  |     0|acc            |   0.1724|±  |  0.0110|
+|              |       |none  |     0|acc_norm       |   0.2201|±  |  0.0121|
+|arc_easy      |      1|none  |     0|acc            |   0.3350|±  |  0.0097|
+|              |       |none  |     0|acc_norm       |   0.3380|±  |  0.0097|
+|boolq         |      2|none  |     0|acc            |   0.4315|±  |  0.0087|
+|hellaswag     |      1|none  |     0|acc            |   0.2614|±  |  0.0044|
+|              |       |none  |     0|acc_norm       |   0.2665|±  |  0.0044|
+|lambada_openai|      1|none  |     0|perplexity     |5951.7544|±  |428.5435|
+|              |       |none  |     0|acc            |   0.0309|±  |  0.0024|
+|openbookqa    |      1|none  |     0|acc            |   0.1460|±  |  0.0158|
+|              |       |none  |     0|acc_norm       |   0.2440|±  |  0.0192|
+|piqa          |      1|none  |     0|acc            |   0.5550|±  |  0.0116|
+|              |       |none  |     0|acc_norm       |   0.5501|±  |  0.0116|
+|sciq          |      1|none  |     0|acc            |   0.4010|±  |  0.0155|
+|              |       |none  |     0|acc_norm       |   0.5070|±  |  0.0158|
+|wikitext      |      2|none  |     0|word_perplexity| 547.6920|±  |N/A     |
+|              |       |none  |     0|byte_perplexity|   3.2518|±  |N/A     |
+|              |       |none  |     0|bits_per_byte  |   1.7012|±  |N/A     |
+|winogrande    |      1|none  |     0|acc            |   0.4822|±  |  0.0140|
+
+hf (pretrained=lomahony/pythia-70m-helpful-dpo), gen_kwargs: (None), limit: None, num_fewshot: 5, batch_size: 16
+|    Tasks     |Version|Filter|n-shot|    Metric     |  Value   |   | Stderr  |
+|--------------|------:|------|-----:|---------------|---------:|---|---------|
+|arc_challenge |      1|none  |     5|acc            |    0.1886|±  |   0.0114|
+|              |       |none  |     5|acc_norm       |    0.2338|±  |   0.0124|
+|arc_easy      |      1|none  |     5|acc            |    0.3346|±  |   0.0097|
+|              |       |none  |     5|acc_norm       |    0.3308|±  |   0.0097|
+|boolq         |      2|none  |     5|acc            |    0.4028|±  |   0.0086|
+|hellaswag     |      1|none  |     5|acc            |    0.2617|±  |   0.0044|
+|              |       |none  |     5|acc_norm       |    0.2648|±  |   0.0044|
+|lambada_openai|      1|none  |     5|perplexity     |22676.7987|±  |1626.4435|
+|              |       |none  |     5|acc            |    0.0173|±  |   0.0018|
+|openbookqa    |      1|none  |     5|acc            |    0.1640|±  |   0.0166|
+|              |       |none  |     5|acc_norm       |    0.2460|±  |   0.0193|
+|piqa          |      1|none  |     5|acc            |    0.5528|±  |   0.0116|
+|              |       |none  |     5|acc_norm       |    0.5462|±  |   0.0116|
+|sciq          |      1|none  |     5|acc            |    0.3100|±  |   0.0146|
+|              |       |none  |     5|acc_norm       |    0.4220|±  |   0.0156|
+|wikitext      |      2|none  |     5|word_perplexity|  547.6920|±  |N/A      |
+|              |       |none  |     5|byte_perplexity|    3.2518|±  |N/A      |
+|              |       |none  |     5|bits_per_byte  |    1.7012|±  |N/A      |
+|winogrande    |      1|none  |     5|acc            |    0.5201|±  |   0.0140|

config.json

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+{
+  "_name_or_path": "EleutherAI/pythia-70m",
+  "architectures": [
+    "GPTNeoXForCausalLM"
+  ],
+  "attention_dropout": 0.0,
+  "bos_token_id": 0,
+  "classifier_dropout": 0.1,
+  "eos_token_id": 0,
+  "hidden_act": "gelu",
+  "hidden_dropout": 0.0,
+  "hidden_size": 512,
+  "initializer_range": 0.02,
+  "intermediate_size": 2048,
+  "layer_norm_eps": 1e-05,
+  "max_position_embeddings": 2048,
+  "model_type": "gpt_neox",
+  "num_attention_heads": 8,
+  "num_hidden_layers": 6,
+  "rope_scaling": null,
+  "rotary_emb_base": 10000,
+  "rotary_pct": 0.25,
+  "tie_word_embeddings": false,
+  "torch_dtype": "bfloat16",
+  "transformers_version": "4.34.1",
+  "use_cache": true,
+  "use_parallel_residual": true,
+  "vocab_size": 50304
+}

generation_config.json

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+{
+  "_from_model_config": true,
+  "bos_token_id": 0,
+  "eos_token_id": 0,
+  "transformers_version": "4.34.1"
+}

pytorch_model.bin

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special_tokens_map.json

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+  "eos_token": "<|endoftext|>",
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+  "sep_token": "<sep>",
+  "unk_token": "<|endoftext|>"
+}

tokenizer_config.json

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