Model save

README.md

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+---
+library_name: transformers
+license: apache-2.0
+base_model: Snowflake/snowflake-arctic-embed-m-v1.5
+tags:
+- generated_from_trainer
+metrics:
+- precision
+- recall
+- accuracy
+model-index:
+- name: fasttext-quality-score
+  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. -->
+
+# fasttext-quality-score
+
+This model is a fine-tuned version of [Snowflake/snowflake-arctic-embed-m-v1.5](https://huggingface.co/Snowflake/snowflake-arctic-embed-m-v1.5) on an unknown dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.0621
+- Precision: 0.466
+- Recall: 0.5
+- F1 Macro: 0.4824
+- Accuracy: 0.932
+
+## 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: 0.0003
+- train_batch_size: 256
+- eval_batch_size: 128
+- seed: 0
+- distributed_type: multi-GPU
+- num_devices: 8
+- total_train_batch_size: 2048
+- total_eval_batch_size: 1024
+- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
+- lr_scheduler_type: linear
+- num_epochs: 20
+
+### Training results
+
+| Training Loss | Epoch   | Step | Validation Loss | Precision | Recall | F1 Macro | Accuracy |
+|:-------------:|:-------:|:----:|:---------------:|:---------:|:------:|:--------:|:--------:|
+| No log        | 0       | 0    | 0.0657          | 0.466     | 0.5    | 0.4824   | 0.932    |
+| 0.0618        | 4.8309  | 1000 | 0.0622          | 0.466     | 0.5    | 0.4824   | 0.932    |
+| 0.0624        | 9.6618  | 2000 | 0.0621          | 0.466     | 0.5    | 0.4824   | 0.932    |
+| 0.0618        | 14.4928 | 3000 | 0.0621          | 0.466     | 0.5    | 0.4824   | 0.932    |
+| 0.0618        | 19.3237 | 4000 | 0.0621          | 0.466     | 0.5    | 0.4824   | 0.932    |
+
+
+### Framework versions
+
+- Transformers 4.56.1
+- Pytorch 2.6.0a0+ecf3bae40a.nv25.01
+- Datasets 4.0.0
+- Tokenizers 0.22.0

final/config.json

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+{
+  "architectures": [
+    "BertForSequenceClassification"
+  ],
+  "attention_probs_dropout_prob": 0.1,
+  "classifier_dropout": 0.0,
+  "dtype": "float32",
+  "gradient_checkpointing": false,
+  "hidden_act": "gelu",
+  "hidden_dropout_prob": 0.0,
+  "hidden_size": 768,
+  "id2label": {
+    "0": "LABEL_0"
+  },
+  "initializer_range": 0.02,
+  "intermediate_size": 3072,
+  "label2id": {
+    "LABEL_0": 0
+  },
+  "layer_norm_eps": 1e-12,
+  "matryoshka_dimensions": [
+    256
+  ],
+  "max_position_embeddings": 512,
+  "model_type": "bert",
+  "num_attention_heads": 12,
+  "num_hidden_layers": 12,
+  "pad_token_id": 0,
+  "position_embedding_type": "absolute",
+  "problem_type": "regression",
+  "transformers_version": "4.56.1",
+  "type_vocab_size": 2,
+  "use_cache": true,
+  "vocab_size": 30522
+}

final/model.safetensors

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final/special_tokens_map.json

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+{
+  "cls_token": {
+    "content": "[CLS]",
+    "lstrip": false,
+    "normalized": false,
+    "rstrip": false,
+    "single_word": false
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+    "lstrip": false,
+    "normalized": false,
+    "rstrip": false,
+    "single_word": false
+  }
+}

final/tokenizer_config.json

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+{
+  "added_tokens_decoder": {
+    "0": {
+      "content": "[PAD]",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
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+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
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+      "rstrip": false,
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+      "special": true
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+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
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+  "clean_up_tokenization_spaces": true,
+  "cls_token": "[CLS]",
+  "do_lower_case": true,
+  "extra_special_tokens": {},
+  "mask_token": "[MASK]",
+  "max_length": 512,
+  "model_max_length": 512,
+  "pad_to_multiple_of": null,
+  "pad_token": "[PAD]",
+  "pad_token_type_id": 0,
+  "padding_side": "right",
+  "sep_token": "[SEP]",
+  "stride": 0,
+  "strip_accents": null,
+  "tokenize_chinese_chars": true,
+  "tokenizer_class": "BertTokenizer",
+  "truncation_side": "right",
+  "truncation_strategy": "longest_first",
+  "unk_token": "[UNK]"
+}

final/training_args.bin

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