Training in progress, epoch 1
Browse files- README.md +61 -0
- config.json +36 -0
- model.safetensors +3 -0
- pytorch_model.bin +3 -0
- runs/Dec17_18-07-57_pooj/events.out.tfevents.1734439082.pooj.16592.0 +3 -0
- runs/Dec17_18-10-23_pooj/events.out.tfevents.1734439224.pooj.29068.0 +3 -0
- runs/Dec18_12-26-17_pooj/events.out.tfevents.1734504979.pooj.24108.0 +3 -0
- runs/Dec18_12-46-26_pooj/events.out.tfevents.1734506189.pooj.24108.1 +3 -0
- runs/Dec18_13-48-15_pooj/events.out.tfevents.1734509897.pooj.24108.2 +3 -0
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- runs/Mar22_18-57-31_Poojilaptop/events.out.tfevents.1711114056.Poojilaptop.21140.0 +3 -0
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- runs/Mar29_14-55-16_Poojilaptop/events.out.tfevents.1711704318.Poojilaptop.11716.0 +3 -0
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- runs/May16_10-35-02_Poojilaptop/events.out.tfevents.1715835903.Poojilaptop.35000.0 +3 -0
- runs/May21_11-25-10_Poojilaptop/events.out.tfevents.1716270917.Poojilaptop.18476.0 +3 -0
- special_tokens_map.json +7 -0
- spiece.model +3 -0
- tokenizer.json +0 -0
- tokenizer_config.json +58 -0
- training_args.bin +3 -0
- vocab.txt +0 -0
README.md
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---
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license: mit
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base_model: ai4bharat/indic-bert
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tags:
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- generated_from_trainer
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metrics:
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- accuracy
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model-index:
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- name: test_model
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results: []
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---
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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should probably proofread and complete it, then remove this comment. -->
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# test_model
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This model is a fine-tuned version of [ai4bharat/indic-bert](https://huggingface.co/ai4bharat/indic-bert) on the None dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.5251
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- Accuracy: 0.7788
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## Model description
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More information needed
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## Intended uses & limitations
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More information needed
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## Training and evaluation data
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More information needed
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## Training procedure
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### Training hyperparameters
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The following hyperparameters were used during training:
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- learning_rate: 2e-05
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- train_batch_size: 16
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- eval_batch_size: 16
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- seed: 42
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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- lr_scheduler_type: linear
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- num_epochs: 2
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### Training results
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| Training Loss | Epoch | Step | Validation Loss | Accuracy |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|
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| No log | 1.0 | 65 | 0.5317 | 0.7788 |
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| No log | 2.0 | 130 | 0.5251 | 0.7788 |
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### Framework versions
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- Transformers 4.41.2
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- Pytorch 2.3.0+cpu
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- Datasets 2.17.0
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- Tokenizers 0.19.1
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config.json
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{
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"_name_or_path": "monsoon-nlp/tamillion",
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"architectures": [
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"ElectraForSequenceClassification"
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],
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"attention_probs_dropout_prob": 0.1,
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"classifier_dropout": null,
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"embedding_size": 768,
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"hidden_act": "gelu",
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"hidden_dropout_prob": 0.1,
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"hidden_size": 768,
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"initializer_range": 0.02,
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"intermediate_size": 3072,
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"layer_norm_eps": 1e-12,
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"max_position_embeddings": 512,
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"model_type": "electra",
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"num_attention_heads": 12,
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"num_hidden_layers": 12,
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"pad_token_id": 0,
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"pooler_fc_size": 768,
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"pooler_num_attention_heads": 12,
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"pooler_num_fc_layers": 3,
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"pooler_size_per_head": 128,
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"pooler_type": "first_token_transform",
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"position_embedding_type": "absolute",
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"problem_type": "single_label_classification",
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"summary_activation": "gelu",
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"summary_last_dropout": 0.1,
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"summary_type": "first",
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"summary_use_proj": true,
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"torch_dtype": "float32",
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"transformers_version": "4.41.2",
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"type_vocab_size": 2,
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"use_cache": true,
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"vocab_size": 39930
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}
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tokenizer_config.json
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47 |
+
"do_lower_case": false,
|
48 |
+
"lowercase": false,
|
49 |
+
"mask_token": "[MASK]",
|
50 |
+
"model_max_length": 1000000000000000019884624838656,
|
51 |
+
"never_split": null,
|
52 |
+
"pad_token": "[PAD]",
|
53 |
+
"sep_token": "[SEP]",
|
54 |
+
"strip_accents": false,
|
55 |
+
"tokenize_chinese_chars": true,
|
56 |
+
"tokenizer_class": "ElectraTokenizer",
|
57 |
+
"unk_token": "[UNK]"
|
58 |
+
}
|
training_args.bin
ADDED
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
1 |
+
version https://git-lfs.github.com/spec/v1
|
2 |
+
oid sha256:d157ef5759216fbf99bf323230230d362bfaccc93b210c88014c11c80368d827
|
3 |
+
size 5112
|
vocab.txt
ADDED
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|
|