logs/llama-3.1-8b-generic-prompt_rpp_1.02.txt

Submitting job: /common/home/users/d/dh.huang.2023/code/rapget-translation/scripts/eval-mac.sh
Current Directory:
/common/home/users/d/dh.huang.2023/code/rapget-translation
Wed Oct  9 08:45:14 2024       
+-----------------------------------------------------------------------------------------+
| NVIDIA-SMI 550.90.07              Driver Version: 550.90.07      CUDA Version: 12.4     |
|-----------------------------------------+------------------------+----------------------+
| GPU  Name                 Persistence-M | Bus-Id          Disp.A | Volatile Uncorr. ECC |
| Fan  Temp   Perf          Pwr:Usage/Cap |           Memory-Usage | GPU-Util  Compute M. |
|                                         |                        |               MIG M. |
|=========================================+========================+======================|
|   0  NVIDIA L40                     On  |   00000000:01:00.0 Off |                    0 |
| N/A   34C    P8             35W /  300W |       1MiB /  46068MiB |      0%      Default |
|                                         |                        |                  N/A |
+-----------------------------------------+------------------------+----------------------+
                                                                                         
+-----------------------------------------------------------------------------------------+
| Processes:                                                                              |
|  GPU   GI   CI        PID   Type   Process name                              GPU Memory |
|        ID   ID                                                               Usage      |
|=========================================================================================|
|  No running processes found                                                             |
+-----------------------------------------------------------------------------------------+
Linux lagoon 4.18.0-553.5.1.el8_10.x86_64 #1 SMP Thu Jun 6 09:41:19 UTC 2024 x86_64 x86_64 x86_64 GNU/Linux
NAME="Rocky Linux"
VERSION="8.10 (Green Obsidian)"
ID="rocky"
ID_LIKE="rhel centos fedora"
VERSION_ID="8.10"
PLATFORM_ID="platform:el8"
PRETTY_NAME="Rocky Linux 8.10 (Green Obsidian)"
ANSI_COLOR="0;32"
LOGO="fedora-logo-icon"
CPE_NAME="cpe:/o:rocky:rocky:8:GA"
HOME_URL="https://rockylinux.org/"
BUG_REPORT_URL="https://bugs.rockylinux.org/"
SUPPORT_END="2029-05-31"
ROCKY_SUPPORT_PRODUCT="Rocky-Linux-8"
ROCKY_SUPPORT_PRODUCT_VERSION="8.10"
REDHAT_SUPPORT_PRODUCT="Rocky Linux"
REDHAT_SUPPORT_PRODUCT_VERSION="8.10"
Architecture:        x86_64
CPU op-mode(s):      32-bit, 64-bit
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CPU(s):              128
On-line CPU(s) list: 0-127
Thread(s) per core:  2
Core(s) per socket:  64
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NUMA node(s):        1
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CPU family:          25
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CPU min MHz:         1500.0000
BogoMIPS:            4891.15
Virtualization:      AMD-V
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L2 cache:            512K
L3 cache:            32768K
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Flags:               fpu vme de pse tsc msr pae mce cx8 apic sep mtrr pge mca cmov pat pse36 clflush mmx fxsr sse sse2 ht syscall nx mmxext fxsr_opt pdpe1gb rdtscp lm constant_tsc rep_good nopl nonstop_tsc cpuid extd_apicid aperfmperf pni pclmulqdq monitor ssse3 fma cx16 pcid sse4_1 sse4_2 movbe popcnt aes xsave avx f16c rdrand lahf_lm cmp_legacy svm extapic cr8_legacy abm sse4a misalignsse 3dnowprefetch osvw ibs skinit wdt tce topoext perfctr_core perfctr_nb bpext perfctr_llc mwaitx cpb cat_l3 cdp_l3 invpcid_single hw_pstate ssbd mba ibrs ibpb stibp vmmcall fsgsbase bmi1 avx2 smep bmi2 erms invpcid cqm rdt_a rdseed adx smap clflushopt clwb sha_ni xsaveopt xsavec xgetbv1 xsaves cqm_llc cqm_occup_llc cqm_mbm_total cqm_mbm_local clzero irperf xsaveerptr wbnoinvd amd_ppin brs arat npt lbrv svm_lock nrip_save tsc_scale vmcb_clean flushbyasid decodeassists pausefilter pfthreshold v_vmsave_vmload vgif v_spec_ctrl umip pku ospke vaes vpclmulqdq rdpid overflow_recov succor smca fsrm
MemTotal:       527669148 kB
Current Directory:
/common/home/users/d/dh.huang.2023/code/rapget-translation
Evaluating shenzhi-wang/Llama3.1-8B-Chinese-Chat
[nltk_data] Downloading package wordnet to
[nltk_data]     /common/home/users/d/dh.huang.2023/nltk_data...
[nltk_data]   Package wordnet is already up-to-date!
[nltk_data] Downloading package punkt to
[nltk_data]     /common/home/users/d/dh.huang.2023/nltk_data...
[nltk_data]   Package punkt is already up-to-date!
[nltk_data] Downloading package omw-1.4 to
[nltk_data]     /common/home/users/d/dh.huang.2023/nltk_data...
[nltk_data]   Package omw-1.4 is already up-to-date!
[nltk_data] Downloading package wordnet to
[nltk_data]     /common/home/users/d/dh.huang.2023/nltk_data...
[nltk_data]   Package wordnet is already up-to-date!
[nltk_data] Downloading package punkt to
[nltk_data]     /common/home/users/d/dh.huang.2023/nltk_data...
[nltk_data]   Package punkt is already up-to-date!
[nltk_data] Downloading package omw-1.4 to
[nltk_data]     /common/home/users/d/dh.huang.2023/nltk_data...
[nltk_data]   Package omw-1.4 is already up-to-date!
loading env vars from: /common/home/users/d/dh.huang.2023/common2/code/rapget-translation/.env
Adding /common/home/users/d/dh.huang.2023/common2/code/rapget-translation to sys.path
loading: /common/home/users/d/dh.huang.2023/common2/code/rapget-translation/eval_modules/calc_repetitions.py
loading /common/home/users/d/dh.huang.2023/common2/code/rapget-translation/llm_toolkit/translation_utils.py

Fetching 5 files:   0%|          | 0/5 [00:00<?, ?it/s]
Fetching 5 files: 100%|██████████| 5/5 [00:00<00:00, 26379.27it/s]
Lightning automatically upgraded your loaded checkpoint from v1.8.3.post1 to v2.4.0. To apply the upgrade to your files permanently, run `python -m pytorch_lightning.utilities.upgrade_checkpoint ../../../../../../../scratch/users/d/dh.huang.2023/transformers/hub/models--Unbabel--wmt22-comet-da/snapshots/371e9839ca4e213dde891b066cf3080f75ec7e72/checkpoints/model.ckpt`
/common/home/users/d/dh.huang.2023/.conda/envs/llm-perf-bench/lib/python3.11/site-packages/transformers/tokenization_utils_base.py:1617: FutureWarning: `clean_up_tokenization_spaces` was not set. It will be set to `True` by default. This behavior will be deprecated in transformers v4.45, and will be then set to `False` by default. For more details check this issue: https://github.com/huggingface/transformers/issues/31884
  warnings.warn(
Encoder model frozen.
/common/home/users/d/dh.huang.2023/.conda/envs/llm-perf-bench/lib/python3.11/site-packages/pytorch_lightning/core/saving.py:195: Found keys that are not in the model state dict but in the checkpoint: ['encoder.model.embeddings.position_ids']
We will use 90% of the memory on device 0 for storing the model, and 10% for the buffer to avoid OOM. You can set `max_memory` in to a higher value to use more memory (at your own risk).
CUDA is available, we have found  1  GPU(s)
NVIDIA L40
CUDA version: 12.1
shenzhi-wang/Llama3.1-8B-Chinese-Chat llama-factory/saves/Llama3.1-8B-Chinese-Chat/checkpoint-105 False datasets/mac/mac.tsv results/mac-results_rpp_with_mnt_2048_generic_prompt.csv False 2048 1
(0) GPU = NVIDIA L40. Max memory = 44.309 GB.
0.0 GB of memory reserved.
loading model: shenzhi-wang/Llama3.1-8B-Chinese-Chat with adapter: llama-factory/saves/Llama3.1-8B-Chinese-Chat/checkpoint-105

Loading checkpoint shards:   0%|          | 0/4 [00:00<?, ?it/s]
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Loading checkpoint shards: 100%|██████████| 4/4 [00:08<00:00,  2.20s/it]
(2) GPU = NVIDIA L40. Max memory = 44.309 GB.
15.201 GB of memory reserved.
loading train/test data files
DatasetDict({
    train: Dataset({
        features: ['chinese', 'english', 'text', 'prompt'],
        num_rows: 4528
    })
    test: Dataset({
        features: ['chinese', 'english', 'text', 'prompt'],
        num_rows: 1133
    })
})
--------------------------------------------------
chinese: 老耿端起枪，眯缝起一只三角眼，一搂扳机响了枪，冰雹般的金麻雀劈哩啪啦往下落，铁砂子在柳枝间飞迸着，嚓嚓有声。
--------------------------------------------------
english: Old Geng picked up his shotgun, squinted, and pulled the trigger. Two sparrows crashed to the ground like hailstones as shotgun pellets tore noisily through the branches.
--------------------------------------------------
text: You will be given a Chinese sentence to translate. If it is an incomplete sentence, or if you are unsure about the meaning, simply copy the input text as your output. Do not output any additional sentence such as explanation or reasoning.

Chinese: 老耿端起枪，眯缝起一只三角眼，一搂扳机响了枪，冰雹般的金麻雀劈哩啪啦往下落，铁砂子在柳枝间飞迸着，嚓嚓有声。
English:Old Geng picked up his shotgun, squinted, and pulled the trigger. Two sparrows crashed to the ground like hailstones as shotgun pellets tore noisily through the branches.<|eot_id|>
--------------------------------------------------
prompt: You will be given a Chinese sentence to translate. If it is an incomplete sentence, or if you are unsure about the meaning, simply copy the input text as your output. Do not output any additional sentence such as explanation or reasoning.

Chinese: 老耿端起枪，眯缝起一只三角眼，一搂扳机响了枪，冰雹般的金麻雀劈哩啪啦往下落，铁砂子在柳枝间飞迸着，嚓嚓有声。
English:
--------------------------------------------------
chinese: 对我一刻也不能放松。
--------------------------------------------------
english: People shouldn't let up on me for a minute.
--------------------------------------------------
text: You will be given a Chinese sentence to translate. If it is an incomplete sentence, or if you are unsure about the meaning, simply copy the input text as your output. Do not output any additional sentence such as explanation or reasoning.

Chinese: 对我一刻也不能放松。
English:People shouldn't let up on me for a minute.<|eot_id|>
--------------------------------------------------
prompt: You will be given a Chinese sentence to translate. If it is an incomplete sentence, or if you are unsure about the meaning, simply copy the input text as your output. Do not output any additional sentence such as explanation or reasoning.

Chinese: 对我一刻也不能放松。
English:
Evaluating model: shenzhi-wang/Llama3.1-8B-Chinese-Chat/checkpoint-105 on cuda
*** Evaluating with repetition_penalty: 1.02

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GPU available: True (cuda), used: True
TPU available: False, using: 0 TPU cores
HPU available: False, using: 0 HPUs
You are using a CUDA device ('NVIDIA L40') that has Tensor Cores. To properly utilize them, you should set `torch.set_float32_matmul_precision('medium' | 'high')` which will trade-off precision for performance. For more details, read https://pytorch.org/docs/stable/generated/torch.set_float32_matmul_precision.html#torch.set_float32_matmul_precision
LOCAL_RANK: 0 - CUDA_VISIBLE_DEVICES: [0]
SLURM auto-requeueing enabled. Setting signal handlers.
Batch output: [' Old Geng raised his gun, narrowed one eye, and pulled the trigger. The golden sparrows fell like hailstones, and the iron sand flew through the willow branches, making a rattling sound.......................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................']
huggingface/tokenizers: The current process just got forked, after parallelism has already been used. Disabling parallelism to avoid deadlocks...
To disable this warning, you can either:
	- Avoid using `tokenizers` before the fork if possible
	- Explicitly set the environment variable TOKENIZERS_PARALLELISM=(true | false)
huggingface/tokenizers: The current process just got forked, after parallelism has already been used. Disabling parallelism to avoid deadlocks...
To disable this warning, you can either:
	- Avoid using `tokenizers` before the fork if possible
	- Explicitly set the environment variable TOKENIZERS_PARALLELISM=(true | false)
Using default tokenizer.
shenzhi-wang/Llama3.1-8B-Chinese-Chat/checkpoint-105/rpp-1.02 metrics: {'comet': 0.4019592371485661, 'meteor': 0.2020993340187826, 'sacrebleu': {'score': 0.24736965475310835, 'counts': [15504, 5980, 2934, 1592], 'totals': [1845826, 1844693, 1843560, 1842427], 'precisions': [0.8399491609718359, 0.32417318220430175, 0.1591486037883226, 0.08640776540943006], 'bp': 1.0, 'sys_len': 1845826, 'ref_len': 30190}, 'bleu_scores': {'bleu': 0.002473696547531083, 'precisions': [0.00839949160971836, 0.0032417318220430173, 0.0015914860378832259, 0.0008640776540943006], 'brevity_penalty': 1.0, 'length_ratio': 61.14031136137794, 'translation_length': 1845826, 'reference_length': 30190}, 'rouge_scores': {'rouge1': 0.20385893465400057, 'rouge2': 0.10034286676374612, 'rougeL': 0.17958213795292688, 'rougeLsum': 0.1796555800262829}, 'accuracy': 0.0, 'correct_ids': []}
*** Evaluating with repetition_penalty: 1.04
srun: Job step aborted: Waiting up to 17 seconds for job step to finish.

  0%|          | 0/1133 [00:00<?, ?it/s]slurmstepd: error: *** STEP 92957.0 ON lagoon CANCELLED AT 2024-10-13T10:09:58 ***
slurmstepd: error: *** JOB 92957 ON lagoon CANCELLED AT 2024-10-13T10:09:58 ***
Job ID: 92957
Cluster: crimson
User/Group: dh.huang.2023/dh.huang.2023
State: CANCELLED (exit code 0)
Nodes: 1
Cores per node: 10
CPU Utilized: 00:00:02
CPU Efficiency: 0.00% of 40-14:07:50 core-walltime
Job Wall-clock time: 4-01:24:47
Memory Utilized: 8.71 GB
Memory Efficiency: 3.40% of 256.00 GB