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README.md

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----
-license: apache-2.0
----
+---
+license: apache-2.0
+base_model: EleutherAI/pythia-160m-deduped
+tags:
+- generated_from_trainer
+datasets:
+- FineWebSentences
+metrics:
+- accuracy
+model-index:
+- name: pythia-finewebedu
+  results:
+  - task:
+      name: Causal Language Modeling
+      type: text-generation
+    dataset:
+      name: FineWebSentences
+      type: FineWebSentences
+    metrics:
+    - name: Accuracy
+      type: accuracy
+      value: 0.24020533058796614
+---
+
+# pythia-finewebedu
+
+- Generate half intelligible English sentences using a small GPT like model.
+- Will output one sentence at a time.
+
+This model is a fine-tuned version of [EleutherAI/pythia-160m-deduped](https://huggingface.co/EleutherAI/pythia-160m-deduped) on the FineWebSentences dataset.
+It achieves the following results on the evaluation set:
+- Loss: 4.7702
+- Accuracy: 0.2402
+
+## Model description
+
+To generate 10 random sentences starting from an empty string on a CUDA device:
+
+```python
+from transformers import pipeline, set_seed
+
+generator = pipeline('text-generation', model='agentlans/pythia-finewebedu', device='cuda')
+
+set_seed(1234)
+results = generator("", max_length=100, num_return_sequences=10, do_sample=True)
+
+for x in results:
+	print(x['generated_text'])
+```
+
+Output:
+```text
+They are also, you need to get great results at her school.
+According to him the term of the Newer, as an entity of the country.
+- To provide less information to help prevent and respond appropriately, it also seems to take action.
+He was an important historical project that he was going to have a history, but the fact that he lived in the US and then he can move back to where he left.
+By the use of the ESLP and INGELTS OF THE TRAIL ORD and REPORTANCE OR:
+However, the system and the Internet have not been built.
+To bridge your teeth with your teeth of the plaque build up with the new teeth and tartar attachments to the tissues, as those without an orthoker.
+This is more difficult than other to learn the basics of the workbooks, where a few thousand notes the same idea that the author can be seen on the work of the project.)
+This study was that by one of the six states, in the middle of a union that he had to marry or union union.
+- A-Pangana and Pitta, P.A. L. T.C.
+```
+
+## Intended uses & limitations
+
+- For generating short lines of English text
+- Could be useful for
+  - data augmentation
+  - creative inspiration
+  - entertainment
+  - CAPTCHA
+- Can be further finetuned on other data such as:
+  - prompts
+  - famous quotes
+  - news headlines
+  - blog post titles
+
+Limitations include:
+
+- Not guaranteed to make sensible, coherent, or grammatically correct sentences
+- No regard for accuracy or truthfulness whatsoever
+  - It's a bunch of words from a probability model, what do you expect?
+
+## Training and evaluation data
+
+Sentences from [HuggingFaceFW/fineweb-edu](https://huggingface.co/datasets/HuggingFaceFW/fineweb-edu)
+
+## Training procedure
+
+### Training hyperparameters
+
+The following hyperparameters were used during training:
+- learning_rate: 5e-05
+- train_batch_size: 8
+- eval_batch_size: 8
+- seed: 42
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- num_epochs: 3.0
+
+### Training results
+
+No overfitting. Lower loss with Pythia-160m than with Pythia-70m, as expected.
+
+### Framework versions
+
+- Transformers 4.39.3
+- Pytorch 2.3.0+cu121
+- Datasets 2.18.0
+- Tokenizers 0.15.2

all_results.json

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+{
+    "epoch": 3.0,
+    "eval_accuracy": 0.24020533058796614,
+    "eval_loss": 4.770163059234619,
+    "eval_runtime": 62.9055,
+    "eval_samples": 2256,
+    "eval_samples_per_second": 35.863,
+    "eval_steps_per_second": 4.483,
+    "perplexity": 117.93847134973377,
+    "train_loss": 4.941846375870074,
+    "train_runtime": 9096.609,
+    "train_samples": 43013,
+    "train_samples_per_second": 14.185,
+    "train_steps_per_second": 3.547
+}

config.json

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+{
+  "_name_or_path": "EleutherAI/pythia-160m-deduped",
+  "architectures": [
+    "GPTNeoXForCausalLM"
+  ],
+  "attention_bias": true,
+  "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": 768,
+  "initializer_range": 0.02,
+  "intermediate_size": 3072,
+  "layer_norm_eps": 1e-05,
+  "max_position_embeddings": 2048,
+  "model_type": "gpt_neox",
+  "num_attention_heads": 12,
+  "num_hidden_layers": 12,
+  "rope_scaling": null,
+  "rotary_emb_base": 10000,
+  "rotary_pct": 0.25,
+  "tie_word_embeddings": false,
+  "torch_dtype": "float32",
+  "transformers_version": "4.39.3",
+  "use_cache": true,
+  "use_parallel_residual": true,
+  "vocab_size": 50304
+}

eval_results.json

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+{
+    "epoch": 3.0,
+    "eval_accuracy": 0.24020533058796614,
+    "eval_loss": 4.770163059234619,
+    "eval_runtime": 62.9055,
+    "eval_samples": 2256,
+    "eval_samples_per_second": 35.863,
+    "eval_steps_per_second": 4.483,
+    "perplexity": 117.93847134973377
+}

generation_config.json

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+{
+  "_from_model_config": true,
+  "bos_token_id": 0,
+  "eos_token_id": 0,
+  "transformers_version": "4.39.3"
+}

model.safetensors

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+version https://git-lfs.github.com/spec/v1
+oid sha256:34f8e41ef447155af8b77e4d531a1191a504e502a1ba2db07bd9d43a7df273b2
+size 649308728

special_tokens_map.json

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

tokenizer_config.json

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train_results.json

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+{
+    "epoch": 3.0,
+    "train_loss": 4.941846375870074,
+    "train_runtime": 9096.609,
+    "train_samples": 43013,
+    "train_samples_per_second": 14.185,
+    "train_steps_per_second": 3.547
+}