End of training

README.md

@@ -0,0 +1,165 @@
+---
+language:
+- fa
+license: apache-2.0
+base_model: makhataei/Whisper-Small-Common-Voice
+tags:
+- fa-asr
+- generated_from_trainer
+metrics:
+- wer
+model-index:
+- name: Whisper Small Persian
+  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. -->
+
+# Whisper Small Persian
+
+This model is a fine-tuned version of [makhataei/Whisper-Small-Common-Voice](https://huggingface.co/makhataei/Whisper-Small-Common-Voice) on the Ctejarat dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.4755
+- Wer: 26.8240
+
+## 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: 1e-07
+- train_batch_size: 11
+- eval_batch_size: 11
+- seed: 42
+- gradient_accumulation_steps: 8
+- total_train_batch_size: 88
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- lr_scheduler_warmup_steps: 500
+- training_steps: 10000
+
+### Training results
+
+| Training Loss | Epoch   | Step  | Validation Loss | Wer     |
+|:-------------:|:-------:|:-----:|:---------------:|:-------:|
+| 0.9585        | 47.06   | 100   | 0.7643          | 39.2704 |
+| 0.8272        | 94.12   | 200   | 0.7201          | 39.0558 |
+| 0.6499        | 141.18  | 300   | 0.6593          | 39.6996 |
+| 0.4717        | 188.24  | 400   | 0.5965          | 36.2661 |
+| 0.2999        | 235.29  | 500   | 0.5380          | 34.3348 |
+| 0.1746        | 282.35  | 600   | 0.4967          | 34.9785 |
+| 0.0995        | 329.41  | 700   | 0.4795          | 35.8369 |
+| 0.0509        | 376.47  | 800   | 0.4714          | 33.0472 |
+| 0.0248        | 423.53  | 900   | 0.4669          | 30.9013 |
+| 0.0144        | 470.59  | 1000  | 0.4643          | 30.6867 |
+| 0.0093        | 517.65  | 1100  | 0.4625          | 29.8283 |
+| 0.0066        | 564.71  | 1200  | 0.4618          | 29.3991 |
+| 0.0051        | 611.76  | 1300  | 0.4616          | 29.6137 |
+| 0.004         | 658.82  | 1400  | 0.4615          | 29.3991 |
+| 0.0034        | 705.88  | 1500  | 0.4616          | 28.7554 |
+| 0.0026        | 752.94  | 1600  | 0.4618          | 29.1845 |
+| 0.0022        | 800.0   | 1700  | 0.4620          | 28.7554 |
+| 0.0019        | 847.06  | 1800  | 0.4622          | 28.7554 |
+| 0.0017        | 894.12  | 1900  | 0.4623          | 28.7554 |
+| 0.0015        | 941.18  | 2000  | 0.4626          | 28.7554 |
+| 0.0013        | 988.24  | 2100  | 0.4628          | 28.7554 |
+| 0.0012        | 1035.29 | 2200  | 0.4630          | 28.3262 |
+| 0.0011        | 1082.35 | 2300  | 0.4633          | 28.3262 |
+| 0.001         | 1129.41 | 2400  | 0.4634          | 28.3262 |
+| 0.0009        | 1176.47 | 2500  | 0.4636          | 28.3262 |
+| 0.0008        | 1223.53 | 2600  | 0.4638          | 28.3262 |
+| 0.0008        | 1270.59 | 2700  | 0.4640          | 27.8970 |
+| 0.0007        | 1317.65 | 2800  | 0.4641          | 28.3262 |
+| 0.0007        | 1364.71 | 2900  | 0.4644          | 28.3262 |
+| 0.0006        | 1411.76 | 3000  | 0.4645          | 28.1116 |
+| 0.0006        | 1458.82 | 3100  | 0.4647          | 27.8970 |
+| 0.0005        | 1505.88 | 3200  | 0.4648          | 27.8970 |
+| 0.0005        | 1552.94 | 3300  | 0.4650          | 28.1116 |
+| 0.0005        | 1600.0  | 3400  | 0.4652          | 28.1116 |
+| 0.0005        | 1647.06 | 3500  | 0.4654          | 27.8970 |
+| 0.0004        | 1694.12 | 3600  | 0.4656          | 27.8970 |
+| 0.0004        | 1741.18 | 3700  | 0.4657          | 27.8970 |
+| 0.0004        | 1788.24 | 3800  | 0.4659          | 27.8970 |
+| 0.0004        | 1835.29 | 3900  | 0.4661          | 27.4678 |
+| 0.0004        | 1882.35 | 4000  | 0.4662          | 27.4678 |
+| 0.0003        | 1929.41 | 4100  | 0.4664          | 27.4678 |
+| 0.0003        | 1976.47 | 4200  | 0.4666          | 27.4678 |
+| 0.0003        | 2023.53 | 4300  | 0.4668          | 27.4678 |
+| 0.0003        | 2070.59 | 4400  | 0.4670          | 27.4678 |
+| 0.0003        | 2117.65 | 4500  | 0.4672          | 27.4678 |
+| 0.0003        | 2164.71 | 4600  | 0.4674          | 27.4678 |
+| 0.0002        | 2211.76 | 4700  | 0.4676          | 27.4678 |
+| 0.0002        | 2258.82 | 4800  | 0.4678          | 27.2532 |
+| 0.0002        | 2305.88 | 4900  | 0.4680          | 27.2532 |
+| 0.0002        | 2352.94 | 5000  | 0.4682          | 27.0386 |
+| 0.0002        | 2400.0  | 5100  | 0.4684          | 27.0386 |
+| 0.0002        | 2447.06 | 5200  | 0.4685          | 27.0386 |
+| 0.0002        | 2494.12 | 5300  | 0.4688          | 27.0386 |
+| 0.0002        | 2541.18 | 5400  | 0.4689          | 27.0386 |
+| 0.0002        | 2588.24 | 5500  | 0.4691          | 27.0386 |
+| 0.0002        | 2635.29 | 5600  | 0.4693          | 27.0386 |
+| 0.0002        | 2682.35 | 5700  | 0.4695          | 27.0386 |
+| 0.0002        | 2729.41 | 5800  | 0.4697          | 27.0386 |
+| 0.0002        | 2776.47 | 5900  | 0.4699          | 27.0386 |
+| 0.0002        | 2823.53 | 6000  | 0.4700          | 27.0386 |
+| 0.0001        | 2870.59 | 6100  | 0.4702          | 27.0386 |
+| 0.0001        | 2917.65 | 6200  | 0.4704          | 27.0386 |
+| 0.0001        | 2964.71 | 6300  | 0.4706          | 27.0386 |
+| 0.0001        | 3011.76 | 6400  | 0.4708          | 27.0386 |
+| 0.0001        | 3058.82 | 6500  | 0.4710          | 27.0386 |
+| 0.0001        | 3105.88 | 6600  | 0.4712          | 27.2532 |
+| 0.0001        | 3152.94 | 6700  | 0.4714          | 27.2532 |
+| 0.0001        | 3200.0  | 6800  | 0.4716          | 27.0386 |
+| 0.0001        | 3247.06 | 6900  | 0.4718          | 27.0386 |
+| 0.0001        | 3294.12 | 7000  | 0.4720          | 27.0386 |
+| 0.0001        | 3341.18 | 7100  | 0.4721          | 27.0386 |
+| 0.0001        | 3388.24 | 7200  | 0.4723          | 26.8240 |
+| 0.0001        | 3435.29 | 7300  | 0.4725          | 26.8240 |
+| 0.0001        | 3482.35 | 7400  | 0.4727          | 26.6094 |
+| 0.0001        | 3529.41 | 7500  | 0.4728          | 26.6094 |
+| 0.0001        | 3576.47 | 7600  | 0.4730          | 26.6094 |
+| 0.0001        | 3623.53 | 7700  | 0.4732          | 26.6094 |
+| 0.0001        | 3670.59 | 7800  | 0.4733          | 26.6094 |
+| 0.0001        | 3717.65 | 7900  | 0.4735          | 26.6094 |
+| 0.0001        | 3764.71 | 8000  | 0.4736          | 26.6094 |
+| 0.0001        | 3811.76 | 8100  | 0.4738          | 26.6094 |
+| 0.0001        | 3858.82 | 8200  | 0.4739          | 26.6094 |
+| 0.0001        | 3905.88 | 8300  | 0.4741          | 26.6094 |
+| 0.0001        | 3952.94 | 8400  | 0.4742          | 26.6094 |
+| 0.0001        | 4000.0  | 8500  | 0.4744          | 26.6094 |
+| 0.0001        | 4047.06 | 8600  | 0.4745          | 26.6094 |
+| 0.0001        | 4094.12 | 8700  | 0.4746          | 26.6094 |
+| 0.0001        | 4141.18 | 8800  | 0.4748          | 26.6094 |
+| 0.0001        | 4188.24 | 8900  | 0.4749          | 26.6094 |
+| 0.0001        | 4235.29 | 9000  | 0.4750          | 26.6094 |
+| 0.0001        | 4282.35 | 9100  | 0.4751          | 26.6094 |
+| 0.0001        | 4329.41 | 9200  | 0.4751          | 27.0386 |
+| 0.0001        | 4376.47 | 9300  | 0.4752          | 27.0386 |
+| 0.0001        | 4423.53 | 9400  | 0.4753          | 27.0386 |
+| 0.0001        | 4470.59 | 9500  | 0.4754          | 27.0386 |
+| 0.0001        | 4517.65 | 9600  | 0.4754          | 27.0386 |
+| 0.0001        | 4564.71 | 9700  | 0.4755          | 26.8240 |
+| 0.0001        | 4611.76 | 9800  | 0.4755          | 26.8240 |
+| 0.0001        | 4658.82 | 9900  | 0.4755          | 26.8240 |
+| 0.0001        | 4705.88 | 10000 | 0.4755          | 26.8240 |
+
+
+### Framework versions
+
+- Transformers 4.35.2
+- Pytorch 2.0.1+cu117
+- Datasets 2.15.0
+- Tokenizers 0.15.0

generation_config.json

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