End of training

.gitattributes

@@ -33,3 +33,4 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
 *.zip filter=lfs diff=lfs merge=lfs -text
 *.zst filter=lfs diff=lfs merge=lfs -text
 *tfevents* filter=lfs diff=lfs merge=lfs -text
+tokenizer.json filter=lfs diff=lfs merge=lfs -text

README.md

@@ -0,0 +1,165 @@
+---
+license: mit
+base_model: xlm-roberta-base
+tags:
+- generated_from_trainer
+model-index:
+- name: xlm-roberta-base-finetuned-ANAD-mlm-0.15-base-25OCT
+  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. -->
+
+# xlm-roberta-base-finetuned-ANAD-mlm-0.15-base-25OCT
+
+This model is a fine-tuned version of [xlm-roberta-base](https://huggingface.co/xlm-roberta-base) on the None dataset.
+It achieves the following results on the evaluation set:
+- Loss: 1.5193
+
+## 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: 5e-05
+- train_batch_size: 8
+- eval_batch_size: 8
+- seed: 42
+- gradient_accumulation_steps: 32
+- total_train_batch_size: 256
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- lr_scheduler_warmup_ratio: 0.1
+- num_epochs: 10
+
+### Training results
+
+| Training Loss | Epoch  | Step  | Validation Loss |
+|:-------------:|:------:|:-----:|:---------------:|
+| No log        | 0.0941 | 100   | 1.9039          |
+| No log        | 0.1881 | 200   | 1.8793          |
+| No log        | 0.2822 | 300   | 1.8643          |
+| No log        | 0.3763 | 400   | 1.8479          |
+| 2.0696        | 0.4703 | 500   | 1.8380          |
+| 2.0696        | 0.5644 | 600   | 1.8336          |
+| 2.0696        | 0.6585 | 700   | 1.8226          |
+| 2.0696        | 0.7525 | 800   | 1.8231          |
+| 2.0696        | 0.8466 | 900   | 1.8136          |
+| 2.0049        | 0.9407 | 1000  | 1.8161          |
+| 2.0049        | 1.0347 | 1100  | 1.8056          |
+| 2.0049        | 1.1288 | 1200  | 1.7934          |
+| 2.0049        | 1.2229 | 1300  | 1.7887          |
+| 2.0049        | 1.3169 | 1400  | 1.7749          |
+| 1.9612        | 1.4110 | 1500  | 1.7726          |
+| 1.9612        | 1.5051 | 1600  | 1.7679          |
+| 1.9612        | 1.5992 | 1700  | 1.7543          |
+| 1.9612        | 1.6932 | 1800  | 1.7473          |
+| 1.9612        | 1.7873 | 1900  | 1.7413          |
+| 1.911         | 1.8814 | 2000  | 1.7334          |
+| 1.911         | 1.9754 | 2100  | 1.7302          |
+| 1.911         | 2.0695 | 2200  | 1.7172          |
+| 1.911         | 2.1636 | 2300  | 1.7187          |
+| 1.911         | 2.2576 | 2400  | 1.7076          |
+| 1.8628        | 2.3517 | 2500  | 1.7011          |
+| 1.8628        | 2.4458 | 2600  | 1.7001          |
+| 1.8628        | 2.5398 | 2700  | 1.6929          |
+| 1.8628        | 2.6339 | 2800  | 1.6929          |
+| 1.8628        | 2.7280 | 2900  | 1.6848          |
+| 1.8328        | 2.8220 | 3000  | 1.6804          |
+| 1.8328        | 2.9161 | 3100  | 1.6762          |
+| 1.8328        | 3.0102 | 3200  | 1.6759          |
+| 1.8328        | 3.1042 | 3300  | 1.6715          |
+| 1.8328        | 3.1983 | 3400  | 1.6653          |
+| 1.8018        | 3.2924 | 3500  | 1.6590          |
+| 1.8018        | 3.3864 | 3600  | 1.6519          |
+| 1.8018        | 3.4805 | 3700  | 1.6493          |
+| 1.8018        | 3.5746 | 3800  | 1.6458          |
+| 1.8018        | 3.6686 | 3900  | 1.6415          |
+| 1.7708        | 3.7627 | 4000  | 1.6397          |
+| 1.7708        | 3.8568 | 4100  | 1.6345          |
+| 1.7708        | 3.9508 | 4200  | 1.6351          |
+| 1.7708        | 4.0449 | 4300  | 1.6324          |
+| 1.7708        | 4.1390 | 4400  | 1.6271          |
+| 1.7501        | 4.2331 | 4500  | 1.6253          |
+| 1.7501        | 4.3271 | 4600  | 1.6248          |
+| 1.7501        | 4.4212 | 4700  | 1.6153          |
+| 1.7501        | 4.5153 | 4800  | 1.6191          |
+| 1.7501        | 4.6093 | 4900  | 1.6135          |
+| 1.7283        | 4.7034 | 5000  | 1.6087          |
+| 1.7283        | 4.7975 | 5100  | 1.6072          |
+| 1.7283        | 4.8915 | 5200  | 1.5991          |
+| 1.7283        | 4.9856 | 5300  | 1.6026          |
+| 1.7283        | 5.0797 | 5400  | 1.5989          |
+| 1.7105        | 5.1737 | 5500  | 1.6011          |
+| 1.7105        | 5.2678 | 5600  | 1.5958          |
+| 1.7105        | 5.3619 | 5700  | 1.5894          |
+| 1.7105        | 5.4559 | 5800  | 1.5871          |
+| 1.7105        | 5.5500 | 5900  | 1.5865          |
+| 1.6816        | 5.6441 | 6000  | 1.5871          |
+| 1.6816        | 5.7381 | 6100  | 1.5840          |
+| 1.6816        | 5.8322 | 6200  | 1.5842          |
+| 1.6816        | 5.9263 | 6300  | 1.5772          |
+| 1.6816        | 6.0203 | 6400  | 1.5769          |
+| 1.6745        | 6.1144 | 6500  | 1.5740          |
+| 1.6745        | 6.2085 | 6600  | 1.5690          |
+| 1.6745        | 6.3025 | 6700  | 1.5700          |
+| 1.6745        | 6.3966 | 6800  | 1.5704          |
+| 1.6745        | 6.4907 | 6900  | 1.5667          |
+| 1.6639        | 6.5847 | 7000  | 1.5653          |
+| 1.6639        | 6.6788 | 7100  | 1.5647          |
+| 1.6639        | 6.7729 | 7200  | 1.5625          |
+| 1.6639        | 6.8670 | 7300  | 1.5572          |
+| 1.6639        | 6.9610 | 7400  | 1.5551          |
+| 1.6509        | 7.0551 | 7500  | 1.5533          |
+| 1.6509        | 7.1492 | 7600  | 1.5522          |
+| 1.6509        | 7.2432 | 7700  | 1.5509          |
+| 1.6509        | 7.3373 | 7800  | 1.5468          |
+| 1.6509        | 7.4314 | 7900  | 1.5488          |
+| 1.6344        | 7.5254 | 8000  | 1.5459          |
+| 1.6344        | 7.6195 | 8100  | 1.5463          |
+| 1.6344        | 7.7136 | 8200  | 1.5452          |
+| 1.6344        | 7.8076 | 8300  | 1.5407          |
+| 1.6344        | 7.9017 | 8400  | 1.5416          |
+| 1.6281        | 7.9958 | 8500  | 1.5400          |
+| 1.6281        | 8.0898 | 8600  | 1.5372          |
+| 1.6281        | 8.1839 | 8700  | 1.5350          |
+| 1.6281        | 8.2780 | 8800  | 1.5341          |
+| 1.6281        | 8.3720 | 8900  | 1.5345          |
+| 1.6132        | 8.4661 | 9000  | 1.5325          |
+| 1.6132        | 8.5602 | 9100  | 1.5293          |
+| 1.6132        | 8.6542 | 9200  | 1.5288          |
+| 1.6132        | 8.7483 | 9300  | 1.5280          |
+| 1.6132        | 8.8424 | 9400  | 1.5287          |
+| 1.6123        | 8.9364 | 9500  | 1.5272          |
+| 1.6123        | 9.0305 | 9600  | 1.5255          |
+| 1.6123        | 9.1246 | 9700  | 1.5251          |
+| 1.6123        | 9.2186 | 9800  | 1.5233          |
+| 1.6123        | 9.3127 | 9900  | 1.5221          |
+| 1.5993        | 9.4068 | 10000 | 1.5223          |
+| 1.5993        | 9.5009 | 10100 | 1.5216          |
+| 1.5993        | 9.5949 | 10200 | 1.5215          |
+| 1.5993        | 9.6890 | 10300 | 1.5207          |
+| 1.5993        | 9.7831 | 10400 | 1.5204          |
+| 1.5959        | 9.8771 | 10500 | 1.5198          |
+| 1.5959        | 9.9712 | 10600 | 1.5193          |
+
+
+### Framework versions
+
+- Transformers 4.43.4
+- Pytorch 2.1.1+cu121
+- Datasets 3.0.2
+- Tokenizers 0.19.1

config.json

@@ -0,0 +1,28 @@
+{
+  "_name_or_path": "xlm-roberta-base",
+  "architectures": [
+    "XLMRobertaForMaskedLM"
+  ],
+  "attention_probs_dropout_prob": 0.1,
+  "bos_token_id": 0,
+  "classifier_dropout": null,
+  "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": "xlm-roberta",
+  "num_attention_heads": 12,
+  "num_hidden_layers": 12,
+  "output_past": true,
+  "pad_token_id": 1,
+  "position_embedding_type": "absolute",
+  "torch_dtype": "float32",
+  "transformers_version": "4.43.4",
+  "type_vocab_size": 1,
+  "use_cache": true,
+  "vocab_size": 250002
+}

model.safetensors

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sentencepiece.bpe.model

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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.json

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tokenizer_config.json

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+{
+  "added_tokens_decoder": {
+    "0": {
+      "content": "<s>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
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+      "lstrip": false,
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+      "lstrip": true,
+      "normalized": false,
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+      "single_word": false,
+      "special": true
+    }
+  },
+  "bos_token": "<s>",
+  "clean_up_tokenization_spaces": true,
+  "cls_token": "<s>",
+  "eos_token": "</s>",
+  "mask_token": "<mask>",
+  "model_max_length": 256,
+  "pad_token": "<pad>",
+  "padding": "max_length",
+  "sep_token": "</s>",
+  "tokenizer_class": "XLMRobertaTokenizer",
+  "truncation": true,
+  "unk_token": "<unk>"
+}

training_args.bin

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