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1_Pooling/config.json

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+{
+  "word_embedding_dimension": 768,
+  "pooling_mode_cls_token": false,
+  "pooling_mode_mean_tokens": true,
+  "pooling_mode_max_tokens": false,
+  "pooling_mode_mean_sqrt_len_tokens": false,
+  "pooling_mode_weightedmean_tokens": false,
+  "pooling_mode_lasttoken": false
+}

README.md

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+---
+license: cc-by-nc-4.0
+pipeline_tag: sentence-similarity
+tags:
+    - sentence-transformers
+    - feature-extraction
+    - sentence-similarity
+    - transformers
+    - generated_from_trainer
+datasets:
+    - squad
+    - newsqa
+    - LLukas22/cqadupstack
+    - LLukas22/fiqa
+    - LLukas22/scidocs
+    - deepset/germanquad
+    - LLukas22/nq
+---
+
+# all-mpnet-base-v2-embedding-all
+
+This model is a fine-tuned version of [all-mpnet-base-v2](https://huggingface.co/sentence-transformers/all-mpnet-base-v2) on the following datasets: [squad](https://huggingface.co/datasets/squad), [newsqa](https://huggingface.co/datasets/newsqa), [LLukas22/cqadupstack](https://huggingface.co/datasets/LLukas22/cqadupstack), [LLukas22/fiqa](https://huggingface.co/datasets/LLukas22/fiqa), [LLukas22/scidocs](https://huggingface.co/datasets/LLukas22/scidocs), [deepset/germanquad](https://huggingface.co/datasets/deepset/germanquad), [LLukas22/nq](https://huggingface.co/datasets/LLukas22/nq).
+
+
+
+## Usage (Sentence-Transformers)
+
+Using this model becomes easy when you have [sentence-transformers](https://www.SBERT.net) installed:
+
+```
+pip install -U sentence-transformers
+```
+
+Then you can use the model like this:
+
+```python
+from sentence_transformers import SentenceTransformer
+sentences = ["This is an example sentence", "Each sentence is converted"]
+
+model = SentenceTransformer('LLukas22/all-mpnet-base-v2-embedding-all')
+embeddings = model.encode(sentences)
+print(embeddings)
+```
+
+## Training hyperparameters
+The following hyperparameters were used during training:
+
+- learning_rate: 1E+00
+- per device batch size: 60
+- effective batch size: 180
+- seed: 42
+- optimizer: AdamW with betas (0.9,0.999) and eps 1E-08
+- weight decay: 2E-02
+- D-Adaptation: True
+- Warmup: True
+- number of epochs: 15
+- mixed_precision_training: bf16
+
+## Training results
+| Epoch | Train Loss | Validation Loss |
+| ----- | ---------- | --------------- |
+| 0 | 0.0554 | 0.047 |
+| 1 | 0.044 | 0.0472 |
+| 2 | 0.0374 | 0.0425 |
+| 3 | 0.0322 | 0.041 |
+| 4 | 0.0278 | 0.0403 |
+| 5 | 0.0246 | 0.0389 |
+| 6 | 0.0215 | 0.0389 |
+| 7 | 0.0192 | 0.0388 |
+| 8 | 0.017 | 0.0379 |
+| 9 | 0.0154 | 0.0375 |
+| 10 | 0.0142 | 0.0381 |
+| 11 | 0.0132 | 0.0372 |
+| 12 | 0.0126 | 0.0377 |
+| 13 | 0.012 | 0.0377 |
+
+## Evaluation results
+| Epoch | top_1 | top_3 | top_5 | top_10 | top_25 |
+| ----- | ----- | ----- | ----- | ----- | ----- |
+| 0 | 0.373 | 0.476 | 0.509 | 0.544 | 0.573 |
+| 1 | 0.362 | 0.466 | 0.501 | 0.537 | 0.568 |
+| 2 | 0.371 | 0.476 | 0.511 | 0.546 | 0.576 |
+| 3 | 0.369 | 0.473 | 0.506 | 0.54 | 0.569 |
+| 4 | 0.373 | 0.478 | 0.512 | 0.547 | 0.578 |
+| 5 | 0.378 | 0.483 | 0.517 | 0.552 | 0.58 |
+| 6 | 0.371 | 0.475 | 0.509 | 0.543 | 0.571 |
+| 7 | 0.379 | 0.484 | 0.517 | 0.55 | 0.578 |
+| 8 | 0.378 | 0.482 | 0.515 | 0.548 | 0.575 |
+| 9 | 0.383 | 0.489 | 0.523 | 0.556 | 0.584 |
+| 10 | 0.38 | 0.483 | 0.517 | 0.549 | 0.575 |
+| 11 | 0.38 | 0.485 | 0.518 | 0.551 | 0.577 |
+| 12 | 0.383 | 0.489 | 0.522 | 0.556 | 0.582 |
+| 13 | 0.385 | 0.49 | 0.523 | 0.555 | 0.581 |
+
+## Framework versions
+- Transformers: 4.25.1
+- PyTorch: 2.0.0.dev20230210+cu118
+- PyTorch Lightning: 1.8.6
+- Datasets: 2.7.1
+- Tokenizers: 0.13.1
+- Sentence Transformers: 2.2.2
+
+## Additional Information
+This model was trained as part of my Master's Thesis **'Evaluation of transformer based language models for use in service information systems'**. The source code is available on [Github](https://github.com/LLukas22/Master).

config.json

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+{
+  "_name_or_path": "sentence-transformers/all-mpnet-base-v2",
+  "architectures": [
+    "MPNetModel"
+  ],
+  "attention_probs_dropout_prob": 0.1,
+  "bos_token_id": 0,
+  "eos_token_id": 2,
+  "hidden_act": "gelu",
+  "hidden_dropout_prob": 0.1,
+  "hidden_size": 768,
+  "initializer_range": 0.02,
+  "intermediate_size": 3072,
+  "layer_norm_eps": 1e-05,
+  "max_position_embeddings": 514,
+  "model_type": "mpnet",
+  "num_attention_heads": 12,
+  "num_hidden_layers": 12,
+  "pad_token_id": 1,
+  "relative_attention_num_buckets": 32,
+  "torch_dtype": "float32",
+  "transformers_version": "4.25.1",
+  "vocab_size": 30527
+}

config_sentence_transformers.json

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+{
+  "__version__": {
+    "sentence_transformers": "2.2.2",
+    "transformers": "4.25.1",
+    "pytorch": "2.0.0.dev20230210+cu118"
+  }
+}

lightning_logs/version_0/events.out.tfevents.1677148612.ki-jupyternotebook-8bdd

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lightning_logs/version_0/hparams.yaml

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modules.json

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+    "name": "0",
+    "path": "",
+    "type": "sentence_transformers.models.Transformer"
+  },
+  {
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+    "name": "1",
+    "path": "1_Pooling",
+    "type": "sentence_transformers.models.Pooling"
+  }
+]

pytorch_model.bin

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sentence_bert_config.json

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+{
+  "max_seq_length": 512,
+  "do_lower_case": false
+}

special_tokens_map.json

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+{
+  "bos_token": "<s>",
+  "cls_token": "<s>",
+  "eos_token": "</s>",
+  "mask_token": {
+    "content": "<mask>",
+    "lstrip": true,
+    "normalized": false,
+    "rstrip": false,
+    "single_word": false
+  },
+  "pad_token": "<pad>",
+  "sep_token": "</s>",
+  "unk_token": "[UNK]"
+}

tokenizer_config.json

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+{
+  "bos_token": "<s>",
+  "cls_token": "<s>",
+  "do_lower_case": true,
+  "eos_token": "</s>",
+  "mask_token": "<mask>",
+  "model_max_length": 512,
+  "name_or_path": "sentence-transformers/all-mpnet-base-v2",
+  "pad_token": "<pad>",
+  "sep_token": "</s>",
+  "special_tokens_map_file": null,
+  "strip_accents": null,
+  "tokenize_chinese_chars": true,
+  "tokenizer_class": "MPNetTokenizer",
+  "unk_token": "[UNK]"
+}