End of training

cc1bdc6 verified 6 months ago

6.16 kB

	---
	license: apache-2.0
	base_model: bert-base-multilingual-uncased
	tags:
	- generated_from_trainer
	metrics:
	- precision
	- recall
	- f1
	- accuracy
	model-index:
	- name: bert_multi-uncased-finetuned-pos-tr
	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. -->

	# bert_multi-uncased-finetuned-pos-tr

	This model is a fine-tuned version of [bert-base-multilingual-uncased](https://huggingface.co/bert-base-multilingual-uncased) on the None dataset.
	It achieves the following results on the evaluation set:
	- Loss: 0.3933
	- Precision: 0.9225
	- Recall: 0.9275
	- F1: 0.9250
	- Accuracy: 0.9564

	## 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: 2e-05
	- train_batch_size: 16
	- eval_batch_size: 16
	- seed: 42
	- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
	- lr_scheduler_type: linear
	- num_epochs: 50

	### Training results

	\| Training Loss \| Epoch \| Step \| Validation Loss \| Precision \| Recall \| F1 \| Accuracy \|
	\|:-------------:\|:-----:\|:-----:\|:---------------:\|:---------:\|:------:\|:------:\|:--------:\|
	\| 0.4051 \| 1.0 \| 836 \| 0.1752 \| 0.9110 \| 0.9098 \| 0.9104 \| 0.9493 \|
	\| 0.1506 \| 2.0 \| 1672 \| 0.1492 \| 0.9112 \| 0.9207 \| 0.9159 \| 0.9529 \|
	\| 0.1182 \| 3.0 \| 2508 \| 0.1632 \| 0.9183 \| 0.9229 \| 0.9206 \| 0.9552 \|
	\| 0.0973 \| 4.0 \| 3344 \| 0.1544 \| 0.9197 \| 0.9216 \| 0.9206 \| 0.9550 \|
	\| 0.0796 \| 5.0 \| 4180 \| 0.1676 \| 0.9227 \| 0.9221 \| 0.9224 \| 0.9569 \|
	\| 0.0673 \| 6.0 \| 5016 \| 0.1829 \| 0.9196 \| 0.9206 \| 0.9201 \| 0.9548 \|
	\| 0.052 \| 7.0 \| 5852 \| 0.1850 \| 0.9220 \| 0.9237 \| 0.9228 \| 0.9562 \|
	\| 0.0448 \| 8.0 \| 6688 \| 0.1980 \| 0.9187 \| 0.9305 \| 0.9246 \| 0.9571 \|
	\| 0.0394 \| 9.0 \| 7524 \| 0.2298 \| 0.9147 \| 0.9204 \| 0.9176 \| 0.9531 \|
	\| 0.0298 \| 10.0 \| 8360 \| 0.2288 \| 0.9217 \| 0.9277 \| 0.9247 \| 0.9571 \|
	\| 0.028 \| 11.0 \| 9196 \| 0.2434 \| 0.9173 \| 0.9231 \| 0.9202 \| 0.9545 \|
	\| 0.0233 \| 12.0 \| 10032 \| 0.2609 \| 0.9174 \| 0.9275 \| 0.9225 \| 0.9558 \|
	\| 0.018 \| 13.0 \| 10868 \| 0.2701 \| 0.9211 \| 0.9249 \| 0.9230 \| 0.9559 \|
	\| 0.0168 \| 14.0 \| 11704 \| 0.2694 \| 0.9206 \| 0.9261 \| 0.9234 \| 0.9564 \|
	\| 0.0157 \| 15.0 \| 12540 \| 0.2774 \| 0.9213 \| 0.929 \| 0.9251 \| 0.9568 \|
	\| 0.0148 \| 16.0 \| 13376 \| 0.2923 \| 0.9229 \| 0.9255 \| 0.9242 \| 0.9565 \|
	\| 0.013 \| 17.0 \| 14212 \| 0.2853 \| 0.9229 \| 0.9263 \| 0.9246 \| 0.9574 \|
	\| 0.0104 \| 18.0 \| 15048 \| 0.2899 \| 0.9224 \| 0.9265 \| 0.9245 \| 0.9569 \|
	\| 0.0096 \| 19.0 \| 15884 \| 0.2769 \| 0.9239 \| 0.9253 \| 0.9246 \| 0.9571 \|
	\| 0.009 \| 20.0 \| 16720 \| 0.3074 \| 0.9204 \| 0.9267 \| 0.9235 \| 0.9570 \|
	\| 0.0098 \| 21.0 \| 17556 \| 0.2985 \| 0.9221 \| 0.9287 \| 0.9254 \| 0.9573 \|
	\| 0.0071 \| 22.0 \| 18392 \| 0.3293 \| 0.9216 \| 0.9277 \| 0.9246 \| 0.9561 \|
	\| 0.0069 \| 23.0 \| 19228 \| 0.3135 \| 0.9242 \| 0.9285 \| 0.9263 \| 0.9572 \|
	\| 0.007 \| 24.0 \| 20064 \| 0.3098 \| 0.9226 \| 0.9291 \| 0.9258 \| 0.9576 \|
	\| 0.0072 \| 25.0 \| 20900 \| 0.3352 \| 0.9241 \| 0.9288 \| 0.9265 \| 0.9580 \|
	\| 0.0048 \| 26.0 \| 21736 \| 0.3384 \| 0.9228 \| 0.9269 \| 0.9249 \| 0.9567 \|
	\| 0.006 \| 27.0 \| 22572 \| 0.3316 \| 0.9232 \| 0.9276 \| 0.9254 \| 0.9575 \|
	\| 0.0057 \| 28.0 \| 23408 \| 0.3381 \| 0.9238 \| 0.9272 \| 0.9255 \| 0.9578 \|
	\| 0.0051 \| 29.0 \| 24244 \| 0.3494 \| 0.9211 \| 0.9282 \| 0.9246 \| 0.9568 \|
	\| 0.0046 \| 30.0 \| 25080 \| 0.3379 \| 0.9237 \| 0.9254 \| 0.9246 \| 0.9570 \|
	\| 0.0044 \| 31.0 \| 25916 \| 0.3512 \| 0.9232 \| 0.9251 \| 0.9242 \| 0.9565 \|
	\| 0.0037 \| 32.0 \| 26752 \| 0.3625 \| 0.9227 \| 0.9252 \| 0.9240 \| 0.9563 \|
	\| 0.0029 \| 33.0 \| 27588 \| 0.3476 \| 0.9220 \| 0.9264 \| 0.9242 \| 0.9574 \|
	\| 0.0039 \| 34.0 \| 28424 \| 0.3635 \| 0.9238 \| 0.9275 \| 0.9257 \| 0.9575 \|
	\| 0.0034 \| 35.0 \| 29260 \| 0.3685 \| 0.9205 \| 0.9247 \| 0.9226 \| 0.9554 \|
	\| 0.0033 \| 36.0 \| 30096 \| 0.3693 \| 0.9219 \| 0.9245 \| 0.9232 \| 0.9555 \|
	\| 0.003 \| 37.0 \| 30932 \| 0.3698 \| 0.9239 \| 0.9257 \| 0.9248 \| 0.9573 \|
	\| 0.0024 \| 38.0 \| 31768 \| 0.3772 \| 0.9242 \| 0.926 \| 0.9251 \| 0.9570 \|
	\| 0.0029 \| 39.0 \| 32604 \| 0.3798 \| 0.9246 \| 0.9281 \| 0.9263 \| 0.9563 \|
	\| 0.0024 \| 40.0 \| 33440 \| 0.3804 \| 0.9215 \| 0.9264 \| 0.9239 \| 0.9562 \|
	\| 0.0017 \| 41.0 \| 34276 \| 0.3804 \| 0.9238 \| 0.9274 \| 0.9256 \| 0.9570 \|
	\| 0.0025 \| 42.0 \| 35112 \| 0.3808 \| 0.9252 \| 0.9273 \| 0.9263 \| 0.9570 \|
	\| 0.0025 \| 43.0 \| 35948 \| 0.3794 \| 0.9237 \| 0.9282 \| 0.9259 \| 0.9568 \|
	\| 0.0029 \| 44.0 \| 36784 \| 0.3784 \| 0.9249 \| 0.9282 \| 0.9265 \| 0.9576 \|
	\| 0.0019 \| 45.0 \| 37620 \| 0.3895 \| 0.9238 \| 0.9281 \| 0.9259 \| 0.9569 \|
	\| 0.0019 \| 46.0 \| 38456 \| 0.3859 \| 0.9238 \| 0.9284 \| 0.9261 \| 0.9572 \|
	\| 0.0017 \| 47.0 \| 39292 \| 0.3906 \| 0.9222 \| 0.9277 \| 0.9249 \| 0.9567 \|
	\| 0.0016 \| 48.0 \| 40128 \| 0.3933 \| 0.9221 \| 0.9273 \| 0.9247 \| 0.9565 \|
	\| 0.0016 \| 49.0 \| 40964 \| 0.3924 \| 0.9224 \| 0.9273 \| 0.9248 \| 0.9565 \|
	\| 0.0017 \| 50.0 \| 41800 \| 0.3933 \| 0.9225 \| 0.9275 \| 0.9250 \| 0.9564 \|


	### Framework versions

	- Transformers 4.34.1
	- Pytorch 2.2.1+cu118
	- Datasets 2.14.6
	- Tokenizers 0.14.1

	---
	license: apache-2.0
	base_model: bert-base-multilingual-uncased
	tags:
	- generated_from_trainer
	metrics:
	- precision
	- recall
	- f1
	- accuracy
	model-index:
	- name: bert_multi-uncased-finetuned-pos-tr
	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. -->

	# bert_multi-uncased-finetuned-pos-tr

	This model is a fine-tuned version of [bert-base-multilingual-uncased](https://huggingface.co/bert-base-multilingual-uncased) on the None dataset.
	It achieves the following results on the evaluation set:
	- Loss: 0.3933
	- Precision: 0.9225
	- Recall: 0.9275
	- F1: 0.9250
	- Accuracy: 0.9564

	## 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: 2e-05
	- train_batch_size: 16
	- eval_batch_size: 16
	- seed: 42
	- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
	- lr_scheduler_type: linear
	- num_epochs: 50

	### Training results

	\| Training Loss \| Epoch \| Step \| Validation Loss \| Precision \| Recall \| F1 \| Accuracy \|
	\|:-------------:\|:-----:\|:-----:\|:---------------:\|:---------:\|:------:\|:------:\|:--------:\|
	\| 0.4051 \| 1.0 \| 836 \| 0.1752 \| 0.9110 \| 0.9098 \| 0.9104 \| 0.9493 \|
	\| 0.1506 \| 2.0 \| 1672 \| 0.1492 \| 0.9112 \| 0.9207 \| 0.9159 \| 0.9529 \|
	\| 0.1182 \| 3.0 \| 2508 \| 0.1632 \| 0.9183 \| 0.9229 \| 0.9206 \| 0.9552 \|
	\| 0.0973 \| 4.0 \| 3344 \| 0.1544 \| 0.9197 \| 0.9216 \| 0.9206 \| 0.9550 \|
	\| 0.0796 \| 5.0 \| 4180 \| 0.1676 \| 0.9227 \| 0.9221 \| 0.9224 \| 0.9569 \|
	\| 0.0673 \| 6.0 \| 5016 \| 0.1829 \| 0.9196 \| 0.9206 \| 0.9201 \| 0.9548 \|
	\| 0.052 \| 7.0 \| 5852 \| 0.1850 \| 0.9220 \| 0.9237 \| 0.9228 \| 0.9562 \|
	\| 0.0448 \| 8.0 \| 6688 \| 0.1980 \| 0.9187 \| 0.9305 \| 0.9246 \| 0.9571 \|
	\| 0.0394 \| 9.0 \| 7524 \| 0.2298 \| 0.9147 \| 0.9204 \| 0.9176 \| 0.9531 \|
	\| 0.0298 \| 10.0 \| 8360 \| 0.2288 \| 0.9217 \| 0.9277 \| 0.9247 \| 0.9571 \|
	\| 0.028 \| 11.0 \| 9196 \| 0.2434 \| 0.9173 \| 0.9231 \| 0.9202 \| 0.9545 \|
	\| 0.0233 \| 12.0 \| 10032 \| 0.2609 \| 0.9174 \| 0.9275 \| 0.9225 \| 0.9558 \|
	\| 0.018 \| 13.0 \| 10868 \| 0.2701 \| 0.9211 \| 0.9249 \| 0.9230 \| 0.9559 \|
	\| 0.0168 \| 14.0 \| 11704 \| 0.2694 \| 0.9206 \| 0.9261 \| 0.9234 \| 0.9564 \|
	\| 0.0157 \| 15.0 \| 12540 \| 0.2774 \| 0.9213 \| 0.929 \| 0.9251 \| 0.9568 \|
	\| 0.0148 \| 16.0 \| 13376 \| 0.2923 \| 0.9229 \| 0.9255 \| 0.9242 \| 0.9565 \|
	\| 0.013 \| 17.0 \| 14212 \| 0.2853 \| 0.9229 \| 0.9263 \| 0.9246 \| 0.9574 \|
	\| 0.0104 \| 18.0 \| 15048 \| 0.2899 \| 0.9224 \| 0.9265 \| 0.9245 \| 0.9569 \|
	\| 0.0096 \| 19.0 \| 15884 \| 0.2769 \| 0.9239 \| 0.9253 \| 0.9246 \| 0.9571 \|
	\| 0.009 \| 20.0 \| 16720 \| 0.3074 \| 0.9204 \| 0.9267 \| 0.9235 \| 0.9570 \|
	\| 0.0098 \| 21.0 \| 17556 \| 0.2985 \| 0.9221 \| 0.9287 \| 0.9254 \| 0.9573 \|
	\| 0.0071 \| 22.0 \| 18392 \| 0.3293 \| 0.9216 \| 0.9277 \| 0.9246 \| 0.9561 \|
	\| 0.0069 \| 23.0 \| 19228 \| 0.3135 \| 0.9242 \| 0.9285 \| 0.9263 \| 0.9572 \|
	\| 0.007 \| 24.0 \| 20064 \| 0.3098 \| 0.9226 \| 0.9291 \| 0.9258 \| 0.9576 \|
	\| 0.0072 \| 25.0 \| 20900 \| 0.3352 \| 0.9241 \| 0.9288 \| 0.9265 \| 0.9580 \|
	\| 0.0048 \| 26.0 \| 21736 \| 0.3384 \| 0.9228 \| 0.9269 \| 0.9249 \| 0.9567 \|
	\| 0.006 \| 27.0 \| 22572 \| 0.3316 \| 0.9232 \| 0.9276 \| 0.9254 \| 0.9575 \|
	\| 0.0057 \| 28.0 \| 23408 \| 0.3381 \| 0.9238 \| 0.9272 \| 0.9255 \| 0.9578 \|
	\| 0.0051 \| 29.0 \| 24244 \| 0.3494 \| 0.9211 \| 0.9282 \| 0.9246 \| 0.9568 \|
	\| 0.0046 \| 30.0 \| 25080 \| 0.3379 \| 0.9237 \| 0.9254 \| 0.9246 \| 0.9570 \|
	\| 0.0044 \| 31.0 \| 25916 \| 0.3512 \| 0.9232 \| 0.9251 \| 0.9242 \| 0.9565 \|
	\| 0.0037 \| 32.0 \| 26752 \| 0.3625 \| 0.9227 \| 0.9252 \| 0.9240 \| 0.9563 \|
	\| 0.0029 \| 33.0 \| 27588 \| 0.3476 \| 0.9220 \| 0.9264 \| 0.9242 \| 0.9574 \|
	\| 0.0039 \| 34.0 \| 28424 \| 0.3635 \| 0.9238 \| 0.9275 \| 0.9257 \| 0.9575 \|
	\| 0.0034 \| 35.0 \| 29260 \| 0.3685 \| 0.9205 \| 0.9247 \| 0.9226 \| 0.9554 \|
	\| 0.0033 \| 36.0 \| 30096 \| 0.3693 \| 0.9219 \| 0.9245 \| 0.9232 \| 0.9555 \|
	\| 0.003 \| 37.0 \| 30932 \| 0.3698 \| 0.9239 \| 0.9257 \| 0.9248 \| 0.9573 \|
	\| 0.0024 \| 38.0 \| 31768 \| 0.3772 \| 0.9242 \| 0.926 \| 0.9251 \| 0.9570 \|
	\| 0.0029 \| 39.0 \| 32604 \| 0.3798 \| 0.9246 \| 0.9281 \| 0.9263 \| 0.9563 \|
	\| 0.0024 \| 40.0 \| 33440 \| 0.3804 \| 0.9215 \| 0.9264 \| 0.9239 \| 0.9562 \|
	\| 0.0017 \| 41.0 \| 34276 \| 0.3804 \| 0.9238 \| 0.9274 \| 0.9256 \| 0.9570 \|
	\| 0.0025 \| 42.0 \| 35112 \| 0.3808 \| 0.9252 \| 0.9273 \| 0.9263 \| 0.9570 \|
	\| 0.0025 \| 43.0 \| 35948 \| 0.3794 \| 0.9237 \| 0.9282 \| 0.9259 \| 0.9568 \|
	\| 0.0029 \| 44.0 \| 36784 \| 0.3784 \| 0.9249 \| 0.9282 \| 0.9265 \| 0.9576 \|
	\| 0.0019 \| 45.0 \| 37620 \| 0.3895 \| 0.9238 \| 0.9281 \| 0.9259 \| 0.9569 \|
	\| 0.0019 \| 46.0 \| 38456 \| 0.3859 \| 0.9238 \| 0.9284 \| 0.9261 \| 0.9572 \|
	\| 0.0017 \| 47.0 \| 39292 \| 0.3906 \| 0.9222 \| 0.9277 \| 0.9249 \| 0.9567 \|
	\| 0.0016 \| 48.0 \| 40128 \| 0.3933 \| 0.9221 \| 0.9273 \| 0.9247 \| 0.9565 \|
	\| 0.0016 \| 49.0 \| 40964 \| 0.3924 \| 0.9224 \| 0.9273 \| 0.9248 \| 0.9565 \|
	\| 0.0017 \| 50.0 \| 41800 \| 0.3933 \| 0.9225 \| 0.9275 \| 0.9250 \| 0.9564 \|


	### Framework versions

	- Transformers 4.34.1
	- Pytorch 2.2.1+cu118
	- Datasets 2.14.6
	- Tokenizers 0.14.1