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Model: lomahony/pythia-1.4b-helpful-sft
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-1.4b](https://huggingface.co/EleutherAI/pythia-1.4b) supervised finetuned using TRLx library 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/trlx-pythia/tree/main)
+
+[wandb log](https://wandb.ai/lauraomahony999/pythia-sft/runs/ydaj2ks8)
+
+See [Pythia-1.4b](https://huggingface.co/EleutherAI/pythia-1.4b) 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-1.4b-helpful-sft), 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            | 0.2679|±  |0.0129|
+|              |       |none  |     0|acc_norm       | 0.2978|±  |0.0134|
+|arc_easy      |      1|none  |     0|acc            | 0.6120|±  |0.0100|
+|              |       |none  |     0|acc_norm       | 0.5282|±  |0.0102|
+|boolq         |      2|none  |     0|acc            | 0.6260|±  |0.0085|
+|hellaswag     |      1|none  |     0|acc            | 0.4097|±  |0.0049|
+|              |       |none  |     0|acc_norm       | 0.5212|±  |0.0050|
+|lambada_openai|      1|none  |     0|perplexity     | 6.4836|±  |0.1838|
+|              |       |none  |     0|acc            | 0.5789|±  |0.0069|
+|openbookqa    |      1|none  |     0|acc            | 0.2120|±  |0.0183|
+|              |       |none  |     0|acc_norm       | 0.3340|±  |0.0211|
+|piqa          |      1|none  |     0|acc            | 0.7100|±  |0.0106|
+|              |       |none  |     0|acc_norm       | 0.7144|±  |0.0105|
+|sciq          |      1|none  |     0|acc            | 0.8540|±  |0.0112|
+|              |       |none  |     0|acc_norm       | 0.7830|±  |0.0130|
+|wikitext      |      2|none  |     0|word_perplexity|15.8394|±  |N/A   |
+|              |       |none  |     0|byte_perplexity| 1.6763|±  |N/A   |
+|              |       |none  |     0|bits_per_byte  | 0.7453|±  |N/A   |
+|winogrande    |      1|none  |     0|acc            | 0.5872|±  |0.0138|
+
+hf (pretrained=lomahony/pythia-1.4b-helpful-sft), 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            | 0.2892|±  |0.0133|
+|              |       |none  |     5|acc_norm       | 0.3097|±  |0.0135|
+|arc_easy      |      1|none  |     5|acc            | 0.6444|±  |0.0098|
+|              |       |none  |     5|acc_norm       | 0.6309|±  |0.0099|
+|boolq         |      2|none  |     5|acc            | 0.6333|±  |0.0084|
+|hellaswag     |      1|none  |     5|acc            | 0.4065|±  |0.0049|
+|              |       |none  |     5|acc_norm       | 0.5215|±  |0.0050|
+|lambada_openai|      1|none  |     5|perplexity     | 9.7040|±  |0.2887|
+|              |       |none  |     5|acc            | 0.4951|±  |0.0070|
+|openbookqa    |      1|none  |     5|acc            | 0.2220|±  |0.0186|
+|              |       |none  |     5|acc_norm       | 0.3100|±  |0.0207|
+|piqa          |      1|none  |     5|acc            | 0.7029|±  |0.0107|
+|              |       |none  |     5|acc_norm       | 0.7127|±  |0.0106|
+|sciq          |      1|none  |     5|acc            | 0.9170|±  |0.0087|
+|              |       |none  |     5|acc_norm       | 0.9160|±  |0.0088|
+|wikitext      |      2|none  |     5|word_perplexity|15.8394|±  |N/A   |
+|              |       |none  |     5|byte_perplexity| 1.6763|±  |N/A   |
+|              |       |none  |     5|bits_per_byte  | 0.7453|±  |N/A   |
+|winogrande    |      1|none  |     5|acc            | 0.5699|±  |0.0139|
+

config.json

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+{
+  "_name_or_path": "EleutherAI/pythia-1.4b",
+  "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": 2048,
+  "initializer_range": 0.02,
+  "intermediate_size": 8192,
+  "layer_norm_eps": 1e-05,
+  "max_position_embeddings": 2048,
+  "model_type": "gpt_neox",
+  "num_attention_heads": 16,
+  "num_hidden_layers": 24,
+  "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"
+}

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special_tokens_map.json

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

tokenizer_config.json

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